literature review of data acquisition

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3 Data Acquisition and Management

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• Published: February 2009
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Proper management of research conduct is essential to achieving reliable results and maintaining the quality, objectivity, and integrity of research data. The different steps of research should be monitored carefully, and research designs should include built-in safeguards to ensure the quality and integrity of research data. This chapter addresses ethical conduct in different steps of the research process: hypothesis formation, research design, literature review, data collection, data analysis, data interpretation, publication, and data storage. This chapter also discusses methods that can help assure the quality, objectivity, and integrity of research data, such as good research practices (GRPs), standard operating procedures (SOPs), peer review, and data audit.

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• Open access
• Published: 14 May 2024

15 years of Big Data: a systematic literature review

• Davide Tosi 1 ,
• Redon Kokaj 1 &
• Marco Roccetti 2  

Journal of Big Data volume  11 , Article number:  73 ( 2024 ) Cite this article

2515 Accesses

1 Citations

Metrics details

Big Data is still gaining attention as a fundamental building block of the Artificial Intelligence and Machine Learning world. Therefore, a lot of effort has been pushed into Big Data research in the last 15 years. The objective of this Systematic Literature Review is to summarize the current state of the art of the previous 15 years of research about Big Data by providing answers to a set of research questions related to the main application domains for Big Data analytics; the significant challenges and limitations researchers have encountered in Big Data analysis, and emerging research trends and future directions in Big Data. The review follows a predefined procedure that automatically searches five well-known digital libraries. After applying the selection criteria to the results, 189 primary studies were identified as relevant, of which 32 were Systematic Literature Reviews. Required information was extracted from the 32 studies and summarized. Our Systematic Literature Review sketched the picture of 15 years of research in Big Data, identifying application domains, challenges, and future directions in this research field. We believe that a substantial amount of work remains to be done to align and seamlessly integrate Big Data into data-driven advanced software solutions of the future.

Introduction

Over the past 15 years, Big Data has emerged as a foundational pillar providing support to an extensive range of different scientific fields, from medicine and healthcare [ 1 ] to engineering [ 2 ], finance and marketing [ 3 , 4 , 5 ], politics [ 6 ], social networks analysis [ 7 , 8 ], and telecommunications [ 9 ], to cite only a few examples. This 15-year period has witnessed a significant increase in research efforts aimed at unraveling the major problems in Big Data, with an almost innumerable array of potential solutions and data sources [ 10 , 11 , 12 , 13 ]. This has resulted in a boundless world of scientific papers that, in the end, have demonstrated the twofold, ambivalent nature of Big Data. On one side, in fact, we have had a confirmation of the pivotal role played by this scientific field in shaping the technological advancements of our time. On the other side, an approach to the comprehension of Big Data, based on this endless universe of ten of thousand technical papers, each specializing in its specific sector, however natural it might seem, has become not sustainable because it has often made researchers confuse (or mixing) the theory (of Big Data) with the practice or use of it. We cannot ignore that there have also been numerous active attempts to describe the general landscape of Big Data through survey papers. Nonetheless, again, given the vastness of the subject, the majority of them did not shun the trap of pre-formed models and have tried to respond, as closely as possible, to the concrete requirements coming from just one sub-field or from the point of view of a few perspectives. In this complex context, to take at least one step further into the knowledge of the state of the art of Big Data research over the above-mentioned period of time, we have decided to conduct a different form of comprehensive exploration which was not biased by the specificity of some given sectors or confounded by single technical perspectives. To do that, we have adopted the methodology termed systematic literature review (SLR), as proposed by Kitchenham and Charters [ 14 ] in the field of software engineering [ 15 , 16 ]. Although SLR proceeds through a set of well-defined steps, also in this case, an initial choice has to be made regarding the most crucial parameters through which the subject of investigation should be explored. In the case of Big Data, our primary focus has been on gaining insights into the principal application domains of Big Data, unraveling the major challenges and limitations encountered by researchers in the analysis of the typically enormous datasets they manage, and unveiling the emerging trends and directions in future Big Data research.

Guided by the structured methodology imposed by SLR, we hence started with three research questions that matched the points raised before: essentially, (i) most common application domains, (ii) current research challenges and limitations, and (iii) emerging future trends and directions. From this point on, we proceeded following the SLR steps. Basically: first, we translated the three research questions above into specific search terms, through which five different digital libraries were investigated, namely: Scopus , IEEE Explore , ACM Digital Library , SpringerLink and Google Scholar . Upon completion of the search activity (detailed in the following section of this paper), 189 primary studies that matched our generic search criteria were identified. Of these 189, only 32 of these studies were actually reviews. Since the target of our study was to provide a panoramic view of this 15-year Big Data research period, (a) shedding light on the prevalent application domains, (b) highlighting the hurdles faced by researchers, and (c) finally outlining the potential trajectories for future research, we focused on the analysis of just these 32 survey studies.

With this paper, we do not want to conduct a traditional literature review on a very extensive topic like Big Data. Traditional scientific surveys can include many more studies and corresponding papers, and they are mainly built with an eye toward generalizability and inclusion rather than selectivity and relevance. As a consequence, those approaches often bring to us no much more than a mere summary of the topic of interest. SLRs, instead, start from the legitimate presumption to be more than merely a summary of a topic. In essence, they distinguish themselves from ordinary surveys of the available literature because they are specifically built to add to the identification of all publications on a topic also all the following activities: explicit formulation of a search objective, identification and description of a search procedure, definition of criteria for inclusion and exclusion of publications, literature selection, and information extraction only based on a transparent evaluation of the quality of publications. Not only this, but an SLR should also provide insightful information on the current state of research on a topic, starting from a given set of research questions and following a formal methodological procedure, designed to reduce distortions caused by an overly generous and restrictive selection of the literature, while guaranteeing the reliability of the selected publications. Hence, to pursue these objectives, an SLR should start with the definition of the criteria for determining what should be included/excluded before conducting the search. Not to mention that, typically, an SLR should be performed mainly using electronic literature databases. It should be also noticed that such a structured approach should document all the information gathered (and the steps taken as part of this process), with the aim of making the paper selection process completely visible and reproducible [ 17 ].

In the end, we know very well that a point-to-point analysis of the set of almost 320 papers from which we have started our SLR could have brought more (generic) information than that provided by the circa 30 papers finally selected by our SLR. Nonetheless, it is highly likely that this information would have been somewhat redundant, more prone to defects and personal biases, and finally, also more boring to read.

With this SLR, we aim to contribute, in a focused and structured way, to Big Data research in several ways: from one side, we provide researchers with a clear picture of how Big Data application domains changed over time; then, we highlight challenges faced by academia and industry and their evolution in the last 15 years; finally, we sketch a set of open points that researchers will take into consideration in the next future.

We can conclude that, while our collective understanding of Big Data has grown after this investigation, this analysis has underscored again the fact that in this field, a kind of optimal stability emerges in terms of research interests through the even distribution among applications domains/challenges/future trends. From one side, we observe a pervasive adoption of Big Data solutions in all everyday life domains (such as Energy [ 18 ], Smart Cities [ 9 ], and Healthcare [ 19 ].) On the other hand, researchers have spent a lot of effort managing data quality, designing and developing advanced frameworks to manage Big Data in real-time, focusing on security and privacy. However, many challenges still remain open to seamlessly integrate Big Data into data-driven advanced software solutions of the future, such as mitigating energy consumption, optimizing algorithms, increasing framework security with privacy and ethical focus, intersecting Artificial Intelligence and Machine Learning technologies, opening data sets, improving interoperability among different stakeholders, and considering societal and business changes.

The remainder of this paper is organized as follows: in Sect " Research method ", we run the SLR methodology on our Big Data use case (with the definition of our research questions, the search strategy, the inclusion/exclusion criteria, the study quality assessment questionnaire, and the data extraction from primary studies). All this is in the dual attempt to explain the abstract methodology, as well as its application in our field. Section " SLR: implementation " describes how we conducted the review and the results obtained in each stage and step of our SLR; Section " SLR: results " shows our findings, briefly summarizing each of our selected primary studies; Section " Discussion " discusses critically those findings garnering special attention in our analytical process; Section " Threats to validity " discusses the possible threats to the validity of our study; Section " Conclusion " demonstrates the conclusions we drew for our SLR.

A taxonomy of key concepts for Big Data evolution over the last 15 years is presented in Fig.  1 .

Taxonomy of Big Data evolution over the last 15 years

Research method

Research questions.

This SLR has been conducted following the procedure defined by Kitchenham and Charters. As such, in the first step, we defined the research questions (RQ) that will drive the entire review methodology.

As we define the research questions that will guide our SLR, it is crucial to establish a balance between the breadth and depth of our investigation. After careful consideration and to ensure that our review maintains a focused and meaningful scope, it has been decided to narrow down our research questions to the following three:

RQ1 : what are the most common application domains for Big Data analytics, and how have they evolved over time?

RQ2 : what are the major challenges and limitations that researchers have encountered in Big Data analysis, and how have they been addressed?

RQ3 : what are the emerging research trends and directions in Big Data that will likely shape the field in the next 5 to 10 years?

Search strategy

SLR begins by looking for relevant studies related to our research questions. To do this, we find appropriate search terms using the method outlined by Kitchenham and Charters, which suggests to consider three aspects: Population (P), Interventions (I), and Outcomes (O).

We identified the following relevant search terms for each aspect in our review:

Population : Big Data, real-time data analytics, large datasets.

Intervention : methodologies, techniques, domains, architectures, solutions.

Outcomes : research trends, future directions, emerging technologies, challenges, SLR, Systematic Literature Review.

The search string was constructed as follows:

P refers to population terms, I refers to intervention terms and O refers to outcome terms, all of which are connected through boolean operators AND and OR.

Searches string may take the exemplar form like the following:

(“big data” OR “real-time data analytics” OR “large datasets”) AND (“methodologies” OR “techniques” OR “domains” OR “architectures” OR “solutions”) AND (“research trends” OR “future directions” OR “emerging technologies” OR “challenges” OR “SLR” OR “Systematic Literature Review”)

Since we need to find and study primary studies related to our research questions, the selection of appropriate digital libraries/search engines to search for the articles needed is essential. For this reason, it has been decided to use the following state-of-the-art sources:

Scopus : a multidisciplinary database that covers a broad range of research fields.

IEEE Xplore : an invaluable resource for technology and engineering-related SLR.

ACM Digital Library : a comprehensive collection of relevant articles, conference papers, and journals focused on computer science and information technology.

SpringerLink : an extensive collection of academic articles in the fields that align closely with our research interests.

Google Scholar : a freely accessible web search engine that indexes scholarly literature across various disciplines.

We aim to ensure a comprehensive and focused literature search by utilizing these sources, thereby facilitating a thorough and methodical research.

Inclusion/Exclusion criteria

In this stage of the SLR, we need to make an accurate selection of the studies extracted. To do this, we must define some rigorous inclusion/exclusion criteria, to decide which studies are going to be useful for our purpose. To achieve this, studies were excluded based on the following criteria:

Studies published before the 15-year time frame

Studies in languages other than English

Exclude non-academic sources, including blogs, news articles, marketing materials, and reports from non-academic organizations

Studies that are only marginally related to Big Data or the specific topics within our research questions.

In conclusion, all those studies that are not cut off by the exclusion criteria above are to be considered as included. They are called “Primary Studies” (PS).

Study quality assessment

Kitchenham and Charters stresses the necessity of assessing the quality of primary studies to reduce bias and enhance the validity of the evaluation process. In our research, we employ a study quality assessment to make sure that we have only the most relevant results for our research.

To achieve this, we formulated a five question study quality questionnaire, which serves as the foundation for assessing the quality of the primary studies:

QA1 : has the primary study established a well-defined research objective?

QA2 : did the primary study comprehensively describe its research methods and data sources?

QA3 : has the technique or approach undergone a trustworthy validation?

QA4 : has the primary study effectively identified and discussed the significant challenges and limitations encountered in Big Data analysis?

QA5 : are the findings, research trends, and directions clearly presented and directly connected to the study’s objectives or goals?

Hence, we applied the formulated questionnaire to the included PSs to assess their quality. The output of this SLR stage will be discussed in Section 4.

Data extraction

The data extraction process entails gathering relevant information from the chosen primary studies to address the research questions. To facilitate this process, we have created a dedicated data extraction form, as shown in Table  1 . As suggested in Kitchenham and Charters, we used the test-retest process to check the consistency and accuracy of the extracted data with respect to the original sources. After finishing the data extraction for all the selected studies, we randomly selected 3 primary studies and performed a second extraction of the data. No inconsistencies were detected.

SLR: implementation

In this section, we describe step-by-step the implementation and execution of the different stages of our SLR. Figure  2 depicts the search stages followed and the resulting number of primary studies for each stage.

In stage 1, an automated search was performed by applying the search string to the digital libraries. The software used for the management of the references is Zotero (www.zotero.org), a popular choice for SLRs. We began the research using the following research string:

(“big data” OR “real-time data analytics” OR “large datasets”) AND (“methodologies” OR “techniques” OR “domains” OR “architectures” OR “solutions”) AND (“research trends” OR “future directions” OR “emerging technologies” OR “challenges” OR “SLR” OR “Systematic Literature Review”). As a result, we found a total of 4204 studies. The reason for this many results could be attributed mostly to the main topic of this SLR being “Big Data”, a hugely popular field, especially in the last few years.

In stage 2, we used the Zotero’s duplicate identification tool, and we found a total of 25 duplicates. Additionally, 1 duplicate was found manually, bringing the total number of results to 4178 articles.

In stage 3, studies were excluded based on the title and the language. Fortunately, all the documents were in English, so we just needed to focus on the title, eliminating what had no use for our research. This cut down the total number to 553.

In stage 4, we eliminated the articles whose abstracts had marginal or no interest at all to us. At the end of the process, 189 Primary Studies were left, 32 of which were SLRs.

To ensure the best quality possible for our SLR, we have collected generic information on all the 189 studies that passed the Primary Study check. This information is depicted in Figs.  3 and 4 . We then proceeded with an in-depth full-text review for the 32 PSs, which are the main subject of our SLR.

Stages of the applied search strategy

Figure  3 depicts the distribution per year for all the 189 studies. Our SLR focuses on the evolution of Big Data in the last 15 years. In any case, no studies before 2012 were detected. The reason for this could be attributed to the fact that before then Big Data, as a research topic, was not as popular.

Number of filtered primary studies and number of total citations

Figure  4 represents the total number of citations per year for our selected 32 Primary Studies. The graph clearly shows that the most recent studies have not been cited as much. Particularly, even though the studies released in the last two years compose about one third of our selected primary studies (11 out of 32), we can see that they have not been cited as much in comparison to the previous years. The lower citation rate may indicate that recently, researchers have focused more on understudied areas or more recent emerging trends, suggesting that the field of Big Data is currently undergoing an evolution. However, further analysis of the quality, methodology and context of these studies is necessary for more concrete conclusions.

Number of total PSs per year

For further clarity, we elaborated Table  2 to represent the chosen articles by highlighting the first author’s family name, the venue, the title of each PS, and a short introduction that highlights the main findings of each PS. Note that the ”J” indicates that the article has been published in a journal.

To better understand the influence of the selected Primary Studies over time, we created a bubble chart to show the most cited documents by aggregating the PSs with the same publication year (see Fig.  5 ). The size of each bubble is proportional to the number of citations.

Bubble chart showing the number of primary studies and total citations per year of publication

SLR: results

The study of the PSs allowed us to pinpoint exactly which research question (RQ1-RQ3) is answered by each primary study. Table  3 summarizes our findings.

As previously stated, it is important to assess the quality of each study. In subsect. " Study quality assessment ", we developed a brief questionnaire that would help us determine the quality of a primary study. Table  4 shows the results of this quality check. It uses a simple “Yes,” “No,” or “na” (used when we don’t have enough information to answer) to fill out the Quality Assessment questionnaire.

From now on, we will briefly summarize each study and its findings.

PS1—A comprehensive and systematic literature review on the Big Data management techniques in the internet of things [ 20 ]

In this article, the authors explored the Big Data management techniques applied to the internet of things. Big Data was initially applied for healthcare monitoring, smart cities, and industrial systems. Over time, with the evolution of IoT, it expanded to include broader topics: healthcare applications involved health state monitoring and predictive modeling, smart cities encompassed traffic management, energy efficiency and security, while industrial systems employed Big Data to improve scalability and security. The application landscape broadened emphasizing the importance of quality attributes such as performance, efficiency, reliability, and scalability in ensuring the success of Big Data Analytics systems in IoT across ever-evolving domains.

The challenges and open issues in Big Data Analytics within IoT span various dimensions, including centralized architectures, energy consumption in data collection, blockchain limitations, communication challenges, and diverse data features.

For future research, the exploration of AI for intelligent mobile data collection will take on a more relevant role, combining compressive sensing with AI for communication challenges and utilizing new optimization algorithms for data processing. To ensure security and privacy in IoT, Big Data Analytics could involve cryptography mechanisms, a data perception layer and a lightweight framework with AI. Addressing these challenges is essential for advancing Big Data Analytics in the evolving landscape of IoT applications.

PS2—A comprehensive review on Big Data for industries challenges and opportunities [ 21 ]

The article explores the transformative impact of Big Data Analytics in power systems, mineral industries, and manufacturing. In power systems, it revolutionizes fault detection, enables early warning systems and predicts future electricity demand, enhancing reliability and decision-making. For mineral industries, Big Data improves data storage, processing and analytics, optimizing exploration, extraction, and resource management. In manufacturing, it facilitates data-driven decision-making, comprehensive product quality assessment, and streamlined supply chain management for increased operational efficiency.

The study also highlights challenges in implementing Big Data Analytics, emphasizing the crucial need for precise data quality assessment models and secure frameworks. Machine learning and data analytics play a pivotal role in overcoming challenges, particularly in fault detection, load forecasting, and reservoir management. The call for open-source databases and integration with machine learning addresses the scarcity of datasets, reflecting challenges in maximizing Big Data’s potential.

Furthermore, the paper recommends future research trends, including advanced data quality assessment models, frameworks for high-dimensional data and solutions for secure communication. Emphasizing open-source databases and integrating machine learning promotes a collaborative and transparent approach. The call for interpretable models reflects a trend toward understanding and optimizing Big Data Analytics. Overall, these recommendations shape the future direction of Big Data applications in diverse industries.

PS3—A survey on IoT Big Data current status, 13 V’s challenges, and future directions [ 22 ]

The document delves into the landscape of Big Data Analytics, particularly exploring its integration with the Internet of Things. Application domains such as energy, healthcare, transportation, and smart cities emerge prominently. The discussion unfolds how these domains have evolved, signalling a shift towards IoT-driven intelligent applications.

Within this expansive terrain, the study identifies and elucidates 13 major challenges encapsulated by the “13 V’s”. These challenges span traditional aspects like volume, velocity, and variety, extending to less common concerns like vagueness and location-aware data processing. The document also offers innovative solutions, like edge-based processing and semantic representation, as strategies to manage these complex challenges.

In regards to the future, the document outlines emerging trends anticipated to define the Big Data landscape in the coming 5 to 10 years. These include a focus on energy-efficient data acquisition, the integration of machine learning and deep learning for advanced analytics, a strategic emphasis on edge and fog infrastructures, the evolving paradigm of multi-cloud data management, a shift towards data-oriented network addressing, and the increasing adoption of blockchain technology. These trends collectively indicate a trajectory towards more efficient, scalable, and secure practices in Big Data Analytics, particularly within the realm of IoT applications.

PS4—A systematic literature review on features of deep learning in Big Data analytics [ 23 ]

The document navigates the evolution of Big Data, emphasizing challenges and the rise of machine learning, particularly Deep Learning. Machine learning’s widespread use, observed in areas like healthcare and finance, underscores its crucial role. Even in complex data scenarios, its effectiveness is evident, as demonstrated by the U.S. Department of Homeland Security’s success in identifying threats.

Recognizing a gap in existing research, the document proposes a review focusing on Deep Learning in Big Data Analytics. The goal is to explore features like hierarchical layers and high-level abstraction. The study emphasizes Deep Learning’s strength in handling extensive datasets, its versatility, and its ability to prevent over fitting.

This exploration into Big Data’s journey underscores the central role of machine learning. The proposed review, specifically focusing on Deep Learning in Big Data Analytics, not only captures current advancements but also suggests there’s more to discover in the future where Big Data and machine learning intersect.

PS5—A systematic survey of data mining and Big Data analysis in internet of things [ 24 ]

The document navigates through diverse applications of Big Data Analytics, illustrating its transformative journey across sectors. Notably, it tracks the evolution within healthcare and finance, showcasing how Big Data has become integral to these domains over time.

Going further, the research dives into the various challenges of Big Data analysis. It identifies three main challenges: dealing with societal changes, understanding how businesses use IoT, and solving technical issues like security and connectivity. The study emphasizes the need to adapt to society’s changing needs, categorize IoT uses in business and front technical problems for effective Big Data analysis.

Moreover, the research anticipates future trends, in particular the rising importance of Big Data frameworks in handling expansive IoT-generated data. The intersection of these frameworks with data mining in the IoT domain emerges as a pivotal focus, pointing toward exciting possibilities and potential paths for future research in the realm of Big Data.

PS6—Access methods for Big Data: current status and future directions [ 25 ]

The document explores diverse applications of Big Data Analytics in research, education, urban planning, transportation, environmental modeling, energy conservation, and homeland security, emphasizing its transformative potential.

It addresses challenges like heterogeneity, scale, timeliness, privacy, and the evolving processing paradigms due to data volume surpassing computational resources.

Future directions include the need for systems handling structured and unstructured data, embedded analytics for real-time processing, innovative paradigms, application frameworks, and advanced databases ensuring transactional semantics. The research underscores the importance of tools addressing ethical, security, and privacy concerns.

PS7—An industrial Big Data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities [ 26 ]

This research introduces an innovative Big Data pipeline designed for industrial analytics in manufacturing.

The pipeline excels in integrating legacy and smart devices, ensuring cross-network communication, and adhering to open standards, marking a significant evolution in the field. The document showcases the pipeline’s ability to handle complexities, integrate older systems, ensure reliability, and scale efficiently in industrial data analytics.

The future plan involves implementing the pipeline to validate its architecture, particularly in predictive maintenance for Wind Turbines and Air Handling Units, contributing to the evolving landscape of Big Data Analytics.

PS8—Applications of Big Data in emerging management disciplines: a literature review using text mining [ 27 ]

This study explores diverse applications of Big Data Analytics across twelve emerging management domains, emphasizing their dynamic nature over time.

It addresses adoption challenges, focusing on data quality, resource management, and distinguishing between the ability and capability of organizations in using Big Data Analytics. The research underscores the thoughtful adoption of Big Data Analytics and the importance of measuring its business value comprehensively. It acknowledges the difficulty of translating insights into real-time actionable items.

Looking forward, the study proposes a framework connecting emerging management domains with conventional practices, suggesting future research areas in human resources, marketing, sales, strategy, and services. The research emphasizes the need for in-depth exploration to integrate emerging domains into established management practices, providing valuable insights for research and practical application.

PS9—Applying Big Data analytics in higher education: a systematic mapping study [ 28 ]

The document conducts a thorough exploration of Big Data Analytics (BDA) in Higher Education Institutions from 2010 to 2020. It uncovers diverse BDA applications in three domains: Educational Quality, Decision-Making Process, and Information Management.

Challenges in BDA adoption include handling large data volumes, addressing privacy concerns, and dealing with resource constraints. The study emphasizes the need for practical outcomes, automated tools, and validated frameworks.

Despite robust research interest, the field exhibits immaturity, with a prevalence of conference papers indicating an early development stage. The study calls for increased empirical research to fortify the evidence base and foster a more mature BDA integration in higher education.

PS10—Artificial intelligence approaches and mechanisms for Big Data analytics: a systematic study [ 29 ]

The SLR explores AI-driven Big Data Analytics, emphasizing machine learning, knowledge-based reasoning, decision-making algorithms, and search methods. Applications, notably in supervised learning, aim to enhance precision and efficiency but grapple with complexity and scalability issues.

Challenges encompass processing vast, heterogeneous data, ensuring system security, and addressing qualitative parameters. Fog computing emerges as a potential solution, yet security concerns remain under-explored.

Emerging trends spotlight Big Data Analytics for IoT through fog computing, the need for enhanced algorithms handling extensive data, and the necessity to address data quality issues in unstructured formats.

PS11—Bibliometric mining of research directions and trends for Big Data [ 30 ]

The research identifies key application domains, with particular focus on China, and emerging directions such as Machine Learning and Healthcare.

Navigating challenges, the study introduces a semi-automatic method, utilizing blacklists and thesauri to enhance precision in identifying research directions. This favors a balance between automation and expert input.

The study forecasts Big Data’s future using a growth rate criterion, emphasizing Machine Learning and Deep Learning. Moreover, the study suggests applying its methodology not only to Big Data but also to various research areas, such as Machine Learning, showcasing its potential applicability in diverse research areas.

PS12—Big Data adoption: state of the art and research challenges [ 31 ]

The study explores the widespread adoption of Big Data Analytics across diverse sectors such as finance, education, healthcare, and more. It identifies a need for increased research in untapped areas like education and healthcare, suggesting potential transformative effects.

Challenges in current Big Data research include the need for refined theoretical models, adaptable data collection methods, and larger sample sizes to ensure accuracy. The study recommends a mixed-method approach to address these challenges effectively.

The study, although not explicitly stating upcoming trends, suggests a changing research focus in both developing and developed countries. It indicates a growing awareness of untapped opportunities, hinting at a future emphasis on specific situations and new factors in Big Data adoption.

PS13—Big Data analytics for data-driven industry: a review of data sources, tools, challenges, solutions, and research directions [ 32 ]

This research provides a comprehensive overview of Big Data Analytics. Exploring application domains, it traces Big Data’s historical integration across education, healthcare, finance, national security, and Industry 4.0 components like IoT and smart cities.

Delving into challenges, the research highlights skill shortages, dataset management, privacy, scalability, and intellectual property issues. Solutions range from software-defined data management to innovative truthfulness and privacy preservation methods.

Looking ahead, the study identifies some emerging trends: sourcing data from education and diverse IoT devices, refining pre-processing, advancing data management, enhancing privacy, and exploring deep learning methods. These trends forecast a dynamic future for Big Data Analytics, shaping the field in the next years.

PS14—Big Data analytics in healthcare: a systematic literature review and road map for practical implementation [ 33 ]

The paper conducts a thorough examination of Big Data Analytics (BDA) applications in healthcare, introducing the novel Med-BDA architecture.

Notably, the work addresses challenges inherent in BDA (such as increased costs, difficulty in acquiring a relevant skill set, rapidly expanding technology stack, and heightened management overhead), presenting a comprehensive road map to alleviate issues such as cost escalation and skill acquisition hurdles.

The document concludes by outlining the potential for extensions to Med-BDA and its applicability to diverse Big Data domains, showcasing a forward-looking perspective in BDA research and application.

PS15—Big Data analytics in telecommunications: literature review and architecture recommendations [ 34 ]

The document explores Big Data Analytics in TELCO, introducing LambdaTel as a proposed solution for batch and streaming data processing. It discusses Big Data Analytics applications like CRM and Customer Attrition.

Challenges, such as the lack of standardized architecture, are acknowledged. LambdaTel addresses these challenges through a structured approach, emphasizing security and recommending the usage Python.

While not explicitly talking about future trends, the document suggests a commitment to ongoing adaptation, seen in recommendations like Python usage, Dockerized implementation and the application of LambdaTel in a local Telco company for cross-selling/up-selling.

PS16—Big Data analytics meets social media: a systematic review of techniques, open issues, and future directions [ 35 ]

The document highlights social media’s transformative impact in healthcare, emphasizing its role in patient support and disease tracking. It emphasizes leveraging social platforms for patient support, disease prevention, and real-time tracking of contagious diseases.

The review highlights challenges in both content and network-oriented approaches, such as privacy concerns, scalability limitations, and accuracy enhancement with incomplete data. Comprehensive resolution remains an open frontier, requiring innovative solutions for privacy preservation and accurate predictions.

The paper also highlights emerging trends in Big Data Analytics, emphasizing real-time and predictive analysis, and addressing challenges in sentiment analysis. It identifies under explored areas like political and e-commerce applications, underscoring the expanding trajectory of Big Data Analytics. Furthermore, it emphasizes the evolving complexities of linguistic analysis, underlining the need for domain-dependent sentiment analysis, and addressing challenges like sarcasm detection.

PS17—Big Data and its future in computational biology: a literature review [ 36 ]

The document underscores the growing significance of Big Data in computational biology and healthcare, particularly in the conversion of healthcare records into digital formats. It highlights the major application domains, focusing on optimizing health and medical care through electronic health data.

Challenges include the under-utilization of electronic health data and the need to convert raw data into actionable information. Despite increasing interest, the field lacks comprehensive literature reviews.

The document outlines emerging trends in Big Data for computational biology and bio informatics. It emphasizes the pivotal role of volume, variety, and velocity in defining Big Data’s impact on bio informatics. Key technologies, including Hadoop and MapReduce, are discussed, illustrating their significance in the field. The integration of Big Data technology is shown to enhance biological findings and facilitate real-time identification of high-risk patients. However, limitations, such as narrow study focuses, are noted.

PS18—Big Data and sentiment analysis: a comprehensive and systematic literature review [ 37 ]

The document delves into the diverse applications of Big Data Analytics, spotlighting its evolution, notably in sentiment analysis for marketing and disaster response.

Challenges identified include data quality issues and the absence of standardized disaster-related datasets. The limitations of centralized data mining algorithms for distributed systems are acknowledged, urging exploration into other platforms (YARN is directly cited as an example). The analysis underscores the need for immediate and improved performance, emphasizing real-time analysis.

In the future, it is important for researchers to carefully look into specific methods like Hadoop, MapReduce, and deep learning. This will help us better understand what these methods are good at and where they might struggle.

PS19—Big Data applications on the internet of things: a systematic literature review [ 38 ]

This document explores the evolving applications of Big Data, from understanding customer sentiments to enhancing disaster response. Hadoop emerges as a popular framework.

Challenges include robust data acquisition from IoT devices, addressing security concerns and optimizing system scalability.

Future directions involve improving algorithms for efficiency, addressing energy consumption, and exploring the synergy of Big Data and machine learning for emergency systems.

PS20—Big Data in education: a state of the art, limitations, and future research directions [ 39 ]

The paper talks about how Big Data Analytics is used in various areas, especially in education, with a noticeable increase in publications from 2014 to 2019. It highlights important topics like how students behave, creating models, using data for education, improving systems, and adding Big Data (as a topic) to study plans.

Researchers face challenges in employing qualitative methods and data collection techniques, highlighting the need for quantitative approaches and more robust methodologies.

Future research should emphasize quantifying Big Data’s impact, adopting efficient solutions, exploring new tools and developing frameworks for educational applications. Integrating the concept of Big Data into study plans requires significant restructuring and well-designed learning activities.

PS21—Big Data in healthcare—a comprehensive bibliometric analysis of current research trends [ 40 ]

This document unveils the dynamic evolution of Big Data Analytics across diverse application domains, with a notable surge in research activities within the healthcare sector since 2012.

While the study discusses various related studies and challenges in Big Data analysis, it does not directly address or provide specific solutions to those challenges.

Looking ahead, the document reveals emerging trends and directions shaping the future of Big Data Analytics over the next 5 to 10 years. Key themes include data analytics, predictive analytics, and collaborative networks, providing a glimpse into the evolving landscape of research endeavors.

PS22—Big Data life cycle in shop-floor-trends and challenges [ 41 ]

The document explores Big Data Analytics in manufacturing, emphasizing its application domains like maintenance, automation, and decision-making.

Challenges include data measurement errors, high-frequency sampling issues, and the need for real-time processing. The study notes a shift to scalable storage options and highlights the importance of efficient data management.

Emerging trends involve the prominent role of AI and statistical approaches in data processing, coupled with a growing emphasis on data privacy. The study concludes with a call for future work focused on developing a consolidated framework for the Big Data life cycle in manufacturing.

PS23—Big Data testing techniques: taxonomy, challenges and future trends [ 42 ]

The paper explores the shift from traditional to advanced testing methods to address challenges in ETL processes, data quality, and node failures.

Addressing major challenges in Big Data analysis, the paper emphasizes the inadequacy of traditional testing, highlighting specific difficulties like ETL testing, node failure prevention, and unit-level debugging. It showcases evolving strategies employed by researchers to ensure the quality of Big Data systems.

Looking ahead, the document outlines emerging research trends shaping the future of Big Data Analytics. It identifies trends such as combinatorial testing techniques, fault tolerance testing, and model-driven entity reconciliation testing as key areas for future exploration.

PS24—Big Data with cognitive computing: a review for the future [ 43 ]

The paper explores the application domains of Big Data Analytics, highlighting its early stage in conjunction with cognitive computing, particularly in healthcare.

Challenges in adoption are attributed to a perceived lack of strategic value. The study categorizes issues into data, process, and management challenges, emphasizing the potential of integrating cognitive computing to overcome barriers.

Regarding emerging trends, there’s a rising interest in cognitive computing. The research encourages more global collaboration and highlights a gap in understanding how Big Data studies impact decision-making processes.

PS25—Current approaches for executing Big Data science projects-a systematic literature review [ 44 ]

The paper explores the landscape of Big Data Analytics. Regarding the common application domains and their evolution, the study notes a significant increase in articles. Workshops play a crucial role in shaping the trajectory, reflecting a robust and expanding interest in Big Data Analytics, influenced by technological advancements.

It also addresses challenges in Big Data analysis, with a focus on workflows and agility. While acknowledging the conceptual nature of agility papers, a gap between theoretical benefits and practical implementation is underscored, necessitating further exploration to optimize agile frameworks for data science projects.

The study highlights emerging trends in Big Data, emphasizing the need for integrated frameworks in data science. It points out a research gap in standardized approaches, urging further exploration for innovative methodologies.

PS26—Data quality affecting Big Data analytics in smart factories: research themes, issues and methods [ 45 ]

This review explores the growing applications of Big Data Analytics in Smart Factories, emphasizing an upsurge in empirical case studies on production, process monitoring, and quality tracing.

Challenges involve key data quality issues (missing, anomalous, noisy, and old data), as well as ISO-defined data quality dimensions. While technical methods prevail, an integrated approach combining technical and non-technical methods for comprehensive data quality management is highlighted. Theoretical insights focus on data quality dimensions, issues, and resolutions, while practical implications underscore the need for collaboration and integrated methods.

The study calls for future research in frameworks, data quality requirements, and emerging scenarios, contributing to Big Data Analytics evolution in Smart Factories.

PS27—Harnessing Big Data analytics for healthcare: a comprehensive review of frameworks, implications, applications, and impacts [ 46 ]

The study meticulously explores the landscape of Big Data Analytics in healthcare. Noteworthy application domains, such as multi modal data analysis and fusion, natural language processing, and electronic health records, emerge from this exploration.

Some challenges faced in Big Data analysis are presented in the document, highlighting issues like data quality, privacy concerns, and a shortage of skilled professionals. It emphasizes the necessity for interoperability and standardization while identifying ongoing challenges in multi modality, ethical considerations, and bias mitigation.

The research outlines emerging trends and directions in Big Data, emphasizing the importance of ongoing exploration in areas like multi modality, data mining, precision medicine, ethical considerations, and the broader understanding of the Big Data Ecosystem.

PS28—Leveraging Big Data in smart cities: a systematic review [ 47 ]

Big Data Analytics has evolved across diverse domains, expanding from finance and healthcare to smart cities and e-commerce. This evolution has been marked by a transformative impact on industries.

Challenges in Big Data, including security, privacy, and scalability issues, have prompted innovative solutions. Advanced encryption, anonymization techniques, and scalable computing frameworks address these concerns.

Looking ahead, emerging trends highlight the fusion of Big Data with AI, machine learning, and technologies like edge computing. Ethical considerations gain prominence and quantum computing’s potential is explored for handling massive datasets.

PS29—Roles and capabilities of enterprise architecture in Big Data analytics technology adoption and implementation [ 48 ]

The document explores the evolution and current state of Big Data Analytics, highlighting its diverse applications in domains like healthcare and finance.

Researchers have grappled with challenges such as data privacy and scalability, addressing them through innovations like advanced encryption and scalable algorithms.

Looking forward, emerging trends include the integration of Artificial Intelligence and Machine Learning for enhanced analytics and a growing focus on ethics and responsible data use. The intersection of Big Data with edge computing and IoT also opens new frontiers for real-time analytics.

PS30—Security and privacy challenges of Big Data adoption: a qualitative study in telecommunication industry [ 49 ]

The research investigates the evolution of Big Data Analytics applications across diverse domains, emphasizing healthcare, finance, marketing, and telecommunications.

Challenges include data security and privacy, addressed through advanced encryption and privacy-preserving techniques.

In the future, emerging trends highlight explainable AI, ethical data practices, and innovations in handling streaming data, graph databases, and blockchain integration.

PS31—The role of AI, machine learning, and Big Data in digital twinning: a systematic literature review, challenges, and opportunities [ 50 ]

The document explores diverse applications of Big Data Analytics across industries like healthcare, energy, and manufacturing. It underscores the evolution of these applications, highlighting a focus on optimization, diagnostics, and predictive analytics.

Challenges include data collection difficulties, picking the right AI models that are both accurate and fast and the ongoing need for standardization in digital twinning.

The document anticipates future trends, emphasizing the integration of AI, Machine Learning, and Big Data, particularly in digital twinning. It sets the stage for ongoing research in optimizing industrial processes, predictive analytics, healthcare, and smart city implementations.

PS32—The state of the art and taxonomy of Big Data analytics: view from new Big Data framework [ 51 ]

The document extensively explores the landscape of Big Data Analytics, emphasizing the dominant role of Hadoop while acknowledging the rise of Apache Spark in recent years.

Major challenges in the field involve handling diverse data formats, optimizing algorithms for evolving hardware configurations, and bridging the gap between complex systems and end-users through user-friendly visualization techniques.

It anticipates future advancements in applications, specifically in domains like e-commerce and the IoT, while expressing optimism about increased investments in Big Data technology.

In the last 15 years, Big Data has found applications across various domains, evolving over time in line with the evolution of technologies and new business needs. Some of the most common application domains for Big Data Analytics include:

Business and Finance, for example, to detect fraud detection by analyzing large datasets and identifying patterns indicative of fraudulent activities or to study customer behavior, preferences, and trends to improve marketing strategies.

Healthcare, for example, to forecast disease outbreaks, patient admission rates, and treatment outcomes, or to personalize medicine with the analysis of genetic data for ad-hoc treatments.

Retail, for example, to automatically manage and optimize inventories, and stock levels by predicting demands, or to create recommender systems to targeted and segmented customers’ profiles.

Manufacturing, for example, to predict and schedule maintenance needs and potential equipment failures by analyzing sensor data, or to improve product quality by monitoring and analyzing production processes.

Telecommunications, for example, to optimize at real-time network performance and areas for improvement, or to predict customer churn by identifying factors and customers’ behaviors that contribute to customer churn.

Government, Public Services, and Transportation, for example, to plan efficient urban mobility, traffic management, and resource allocation in Smart Cities, or to predict and prevent criminal activities, or to optimize energy distribution and reduce wastage, or to optimize transportation routes, reduce delivery times, and vehicle fleets for efficiency and cost savings.

Media, Entertainment, and Education, for example, to recommend movies, music, or articles based on users’ behaviors and preferences, or to tailor content and advertising by studying users’ behaviors, or to improve educational impact by analyzing student performance.

In Fig.  6 , we show the distribution of the studies addressing the three research questions (RQ1-RQ3), from which we has started initially our investigation: 31 PSs discuss common application domains where the use of Big Data solutions is relevant (RQ1); 30 PSs analyze research challenges and limitations of Big Data (RQ2); 28 PSs highlight emerging research trends and directions in Big Data (RQ3). The total number of papers addressing the 3 RQs is different from the number of the selected 32 PSs, since we observed overlaps and intersections (e.g., a PS can address multiple RQs.)

Distribution of studies addressing the three research questions

To better understand the main focus of the PSs, Fig.  7 shows the distribution of studies addressing the three research questions, but this time, we made it avoiding intersections (i.e., each primary study can only be part of one of the 3 categories.) We can classify 12 PSs as papers that mainly focus on RQ1, 10 PSs mainly focus on RQ2, and 10 PSs on RQ3. The homogeneous distribution of the primary studies allows us to be optimistic about the results of our research since we had a good number of studies to answer each of our research questions.

Distribution of studies mainly addressing the three research questions

To further make clear the main focuses of our studies, we decided to categorize each one. Figures  8 , 9 , and 10 show the focus of the documents for each Research Question (note that the sum of the categorized documents may be greater than the number of studies that answer that RQ, because they may overlap and be part of more than one category).

Categorization of RQ1 studies

Categorization of RQ2 studies

Categorization of RQ3 studies

Having clarified this, we now discuss the findings of our SLR. We divided this discussion in three sections, one for each Research Question, so that we could clearly define which elements answer which question.

RQ1: what are the most common application domains for Big Data analytics, and how have they evolved over time?

Delving into the realm of Big Data across various sectors over the last 15 years reveals a narrative of evolution and adaptation. Initially rooted in finance, healthcare and marketing, the domain of Big Data analytics has undergone a metamorphosis, embracing applications from computational biology to education and manufacturing, expanding into the avant-garde concept of digital twinning. This dynamic evolution is evident in studies investigating Big Data management techniques on the Internet of Things, where the focus has shifted from basic health state monitoring to sophisticated predictive modeling. This evolution signifies a maturation of Big Data analytics, with an increased focus on nuanced attributes like performance, efficiency, reliability, and scalability.

RQ2: what are the major challenges and limitations that researchers have encountered in Big Data analysis, and how have they been addressed?

Shifting our focus to the challenges within the Big Data analytics landscape, a complex history of persistent hurdles and inventive solutions comes into focus. The studies converge on a common thread, unraveling ongoing challenges encapsulated in the trio of data quality, scalability, and privacy/security concerns. Researchers faced with these challenges have become architects of innovative solutions, leveraging advanced algorithms, distributed frameworks, and privacy-preserving techniques. These solutions reflect a commitment to advancing the field in response to the complexities of handling vast and dynamic datasets.

In the implementation of Big Data Analytics, diverse challenges emerge. A dedicated study on industries points to crucial issues in data quality assessment models and secure frameworks. Here, the role of machine learning and data analytics, particularly in fault detection and reservoir management, becomes pivotal. The interconnected nature of these challenges emphasizes the importance of a comprehensive approach to implementation. Beyond technological challenges, ethical considerations surrounding data privacy and security take center stage. Researchers stress the significance of tools addressing ethical concerns, underlining that responsible deployment is intrinsic to the ethical use of Big Data Analytics.

In response to these challenges, the industry advocates for innovative solutions, emphasizing AI-driven approaches, cryptography mechanisms, and lightweight frameworks with AI. This recognition underscores the need for inventive strategies to navigate the intricate integration of Big Data into rapidly evolving technological landscapes.

RQ3: what are the emerging research trends and directions in Big Data that will likely shape the field in the next 5 to 10 years?

Looking into the next 5 to 10 years, several trends are expected to shape the landscape of Big Data Analytics. One significant trend involves making data acquisition more energy-efficient, a move that aligns with broader sustainability goals. The integration of machine learning and deep learning techniques is anticipated to enhance the analytical capabilities of Big Data systems, enabling more accurate predictions and insights. Another noteworthy trend is the emphasis on edge and fog infrastructures, signifying a shift towards decentralized processing for faster data processing and decision-making, especially relevant in the context of the Internet of Things. Importantly, these trends extend beyond technological advancements to include ethical considerations. As Big Data assumes a pivotal role in decision-making processes, these ethical dimensions must be at the forefront. This involves dealing with the tricky ethical issues that come with having such a big influence through data analytics.

In essence, the trajectory of Big Data analytics in the coming years is a dual journey, one that advances technologically with a keen eye on efficiency and, concurrently, prioritizes ethical practices. It’s a future where innovation and responsibility go hand in hand, defining a landscape that reflects both progress and ethical consciousness.

Threats to validity

Ensuring the validity of a SLR is essential for the development of a reliable study. For this reason, in this section, we examine potential threats to construct, internal and external validity, aiming to maintain the robustness of our findings.

Construct validity determines whether the implementation of the SLR aligns with its initial objectives. The efficacy of our search process and the relevance of search terms are crucial concerns. While our search terms were derived from well-defined research questions and adjusted based on that, the completeness and comprehensiveness of these terms may be subject to limitations. Additionally, the use of different keywords might have returned other relevant studies that have not been taken into consideration. A potential language bias may also exist due to the exclusion of non-English articles, representing a limitation that should be acknowledged in the overall validity of the research.

Internal validity assesses the extent to which the design and execution of the study minimize systematic errors. A key focus is on the process of data extraction from the selected primary studies. Some required data may not have been explicitly expressed or were entirely missing, posing a potential threat to internal validity. To minimize this risk, the SLR process has been supervised by another person in order to minimize error into the process.

External validity examines the extent to which the observed effects of the study can be applied beyond its scope. In this SLR, we concentrated on research questions and quality assessments to mitigate the risk of limited generalizability. However, the study’s focus on the specific domain of Big Data research may limit external validity. Moreover, the dynamic nature of Big Data and the predefined time frame (last 15 years) could affect the generalizability of findings. Recognizing these constraints, the outcomes of this SLR are considered generalizable within the specified context of Big Data research.

By acknowledging these potential threats to validity, we strive to enhance the credibility and reliability of our SLR, contributing valuable insights to the evolving landscape of Big Data research.

Over the past 15 years, Big Data has become a crucial player in various fields, adapting to technological shifts and meeting the changing needs of businesses. This review has taken a closer look at how Big Data has been applied, its challenges, and what we can expect in the near future. 189 studies were ultimately found, 32 of which were SLRs analyzed for this study.

Big Data started in areas like Business, Healthcare, and Marketing, but its influence has ultimately grown. Now, it helps predict disease outbreaks, manage retail inventory, forecast equipment failures in manufacturing, improve network performance, optimize urban planning, personalize media content, and enhance education.

Dealing with Big Data hasn’t been without challenges. Issues like ensuring data quality, handling scalability, and maintaining privacy and security have been persistent. Researchers have responded with creative solutions, using advanced algorithms and privacy measures.

Looking to the future, the trends suggest exciting developments. Making data acquisition more energy-efficient and integrating advanced machine learning techniques are on the horizon. There is a shift toward decentralized processing, especially with the Internet of Things in mind. Importantly, these trends aren’t just about technology; they also emphasize ethical considerations. Ethical issues need careful attention as Big Data becomes more influential in decision-making processes.

To summarize, the future of Big Data is a journey that combines technological progress with a strong ethical stance. It’s a path where innovation and responsibility walk hand in hand, shaping a landscape that advances both technologically and ethically. The last 15 years have set the stage and the road ahead invites us to keep exploring and engaging with the ever-evolving world of Big Data.

Data availability

No datasets were generated or analysed during the current study.

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Davide Tosi & Redon Kokaj

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Tosi, D., Kokaj, R. & Roccetti, M. 15 years of Big Data: a systematic literature review. J Big Data 11 , 73 (2024). https://doi.org/10.1186/s40537-024-00914-9

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This literature of acquisitions review is the continuation of the authors’ review covering the literature published from 1996 through 2003. 1 In the previous review, technology and the Internet were the key themes that brought changes to acquisitions, business practices, and communications. For 2004–7, budgets and budget allocation were a continuing concern, with the literature focusing on the complexity and variability of pricing models. The most significant new topic was the management of electronic resources. As patron demand for these resources grew rapidly, a large portion of library materials budgets was spent acquiring them. The literature revealed that acquiring electronic resources was simpler than managing them effectively.

To identify the significant acquisitions literature published from 2004 through 2007, searches were made through Library Literature and Information Science Full Text and Library, Information Science and Technology Abstracts with Full Text databases for articles and books. In addition, searches using more specific terms related to acquisitions were made of selected library journals. Citations and abstracts were reviewed for possible inclusion in the review. Searches were limited to scholarly journal articles, conference proceedings, reports, and books in English. Every attempt was made to find literature relating to any aspect of acquisitions; however, the authors concede that some works may have been overlooked. For those articles selected, the papers were retrieved and reviewed in detail. The selected articles then were grouped by topics to establish an outline for presentation. For those papers that bridged more than one topic, an effort was made to put them under the topic that was most prominent. Some literature fell outside the major themes identified or was peripheral to the topics; these were excluded from the review.

Fund allocation became a critical part of budgeting and acquisitions work as budgets shrank and material costs rose. Most libraries used a local method to allocate the materials budget across subject areas. Many allocation formulas were based on historical variables and annual adjustments that no longer fit the needs of libraries’ current acquisitions.

Wu and Shelfer performed a formula fitness study on their library’s budget allocation formula to determine its fit. 2 The authors’ research indicated that the traditional factors used in building a fund allocation formula were not always consistent because of changes in the source of the data, availability of data, and weights given to the variables. Wu and Shelfer recommended that libraries perform a formula fitness review regularly as a part of their self-study. At Portland State, the old method no longer provided for a balanced collection and failed to align the materials budget with the university’s priorities. 3 Weston revised the formula using a complex set of variables to determine the potential demand on their library’s collection for specific subject areas. Because the new formula would result in severe cuts from the previous allocations, 70 percent of the budget was allocated on the basis of the previous formula. Walters, in an article that received the 2008 Best of LRTS Award, presented an allocation method for academic libraries that used current, historical, or hypothetical allocations to generate a formula. 4 In a five-step process, the regression-based method assigned weight to a set of variables to provide results that were systematic and unbiased.

While most discussion of fund allocation focused on specific approaches for allocating funds, Canepi’s study focused on determining best practices in academic libraries. 5 Her statistical analysis revealed that enrollment, cost of materials, use, and number of faculty were the most frequently used formula elements. Other often-used elements were course offerings, academic programs, research budget or output, and faculty publication.

Smith and Langenkamp discussed an allocation formula for a public library based on circulation data. 6 The authors calculated a budgeting index by multiplying the circulation percentage for a subject area by the average cost of an item. The index was used to determine the number of items that could be purchased from the budget for each subject area. Their method allowed for changes in allocations for specific subject areas on the basis of current collection management goals, pricing changes in subject areas for collection development, and static budget amounts. At Auburn University at Montgomery (AUM) Library, Bailey, Lessels, and Best tested using Universal Borrowing data as a factor in determining their monographic budget allocations across the University’s schools. 7 Universal Borrowing is an interlibrary borrowing feature of the Voyager integrated library system (ILS) that allows patrons to borrow and return materials from any consortial member. The results of the trial revealed that demand could be matched to AUM’s monographic collection across the university. The schools with graduate programs showed the most demand. The authors determined that the data supported additional book purchases. The monographic budget was increased to support the schools with the greatest borrowing activities.

Anderson discussed several formulas of varying complexity for allocating the costs of electronic resources to the members of an academic consortium. 8 Size and type of institution, number of students, size of budget, current use, and current subscription price were considered potential factors in cost-allocation methods. He stressed fairness in the cost-allocation methods and the use of equitable formulas that were clearly understandable.

Clendenning, Martin, and McKenzie examined how libraries managed the relationship between fund encumbrances and expenditures. 9 Various strategies specific to monographs, serials, and standing order acquisitions were studied. The authors’ discussion also included insights on the use of ILSs for managing funds, descriptions of materials ordered on different types of funds, and three fund case studies.

At the 2006 Charleston Conference, Moore-Jansen, Walker, and Williams explained the development of a fund tree, a computer-based accounting system at Wichita State University Libraries. 10 The tree was designed to meet the reporting needs of the library administration, budget officer, collection development coordinators, and acquisition managers. The fund accounting tree utilized a combination of letter mnemonics and a number to form a fund code. The fund code could be used to the track the funds allocated by discipline.

A useful manual about library budgets is Managing Budgets and Finances: A How-to-Do It Manual for Librarians and Informational Professionals by Hallam and Dalston. 11 Their manual covers a broad range of topics on budget and finance. In another source, Collection Management for Youth , Hughes-Hassell and Mancall describe the budgeting process for a school media center in their chapter, “Budgeting for Maximum Impact on Learning.” 12

Johnson’s book, Fundamentals of Collection Development & Management , is intended for students in librarianship or those new to collection development and management. 13 The chapter “Policy, Planning, and Budgets” covers library budgets, materials budget, funds, and fund allocations. In the chapter “Electronic Resources,” Johnson describes electronic resources and covers budget and legal issues associated with their acquisition.

Evans and Saponaro’s text, Developing Library and Information Center Collections , covers collection development for all types of libraries. 14 Separate chapters address acquisitions, vendors and distributors, and fiscal management.

As electronic resources emerged, pricing models became more complex. Publishers and providers developed many new models for electronic journals and e-books. The Big Deal model for electronic journals was the most often discussed in the literature. A Big Deal is defined by Frazier as “a comprehensive licensing agreement in which a library or library consortium agrees to buy electronic access to all or a large portion of a publisher’s journals for a cost based on expenditures for journals already subscribed to by the institution(s) plus an access fee.” 15 Usually the agreement limits the cancellation of subscriptions and includes an annual price increase.

Gerhard described pricing models used for academic electronic journals and other digital formats and examined the variables used in pricing models. 16 She found nine variables that could be combined into a seemingly unending number of pricing options. Gerhard also found that the variety of pricing models provided some formulas that worked in favor of libraries of a certain type and size while other pricing models disadvantaged some libraries. Some formulas also worked better for different types of products depending on content and use.

Hahn took an in-depth look at tiered pricing, in which smaller institutions are assessed a lower subscription price than larger ones. 17 By performing a sensitivity analysis, she found that increases in the subscription price for larger institutions (i.e., those in the top tier) ranged from 7 to 257 percent while institutions in the bottom tiers experienced increases of 9 to 88 percent. Under some models a lower tier could receive a decrease. Hahn believed that the increase in subscriptions costs could be substantial for the largest institutions. Schaffner, Luther, and Ivins described the collaborative effort Project MUSE made to develop new pricing for their online journals. 18 Project Muse replaced the consortial model based on number of participating institutions with one based on the Carnegie Class and use. The pricing tiers for academic libraries were expanded under the new model.

Commissioned by the Journals Working Group of the United Kingdom’s Joint Information Systems Committee, Look, Sparks, and Henderson researched what librarians and publisher thought about existing pricing models and proposed new models. 19 Librarians and publishers were interviewed to understand current models’ strengths and weakness. Views about the Big Deal packages varied by size or focus of an institution, but some broad patterns emerged. The authors found that Big Deal packages squeezed out other purchases, the bundled titles were not always the right ones for a library, and heavy collection penalties made adjusting collections difficult. Universities founded after 1992 with fewer journals favored Big Deal packages but were concerned about future affordability. None of the proposed new models (e.g., pay-per-view, national license, core plus peripheral, open access models) were universally accepted. The publishers were consistent on needing to maintain current levels of profitability.

At the 2005 North American Serials Interest Group conference, Frazier and Ebert discussed the Big Deals. 20 Frazier focused on issues related to budget. With an annual cost increase each year, he considered Big Deals unsustainable because budgets would be unable to keep pace with the increasing costs of journals. Frazier focused on journal cost-effectiveness for purchases. Ebert looked at the Big Deal from a consortial perspective. Big Deals allowed consortial members to reduce duplication and increase the number of unique titles. Because unused titles could be an issue, she noted that the consortium monitored the use of bundled titles and considered 85 percent of the titles used acceptable.

Gatten and Sanville discussed the merits of the Big Deal from the OhioLINK consortial perspective. 21 They defined Big Deal as “the subscription and purchase of full sets of publisher’s journals in electronic format and the provision of access to member institutions.” 22 Because the financial commitment of a Big Deal could present challenges to institutions when budgets are static or shrinking, an incremental reduction of content and related annual costs were negotiated in the license agreements with vendors. The authors questioned if patterns of use across the members would allow for a title-by-title retreat without disenfranchising one or more members. Their findings supported the concept that a retreat based on the ranking of articles downloaded across members would be a workable approach for reducing content and costs.

Hellriegel and Van Wonterghem examined electronic journal packages and their effect on library budgets and consortia purchases. 23 They discussed the development of package deals, the effect of their increased costs when budgets decrease, issues associated with cancellations when involved in Big Deal license agreements, and the effect on cost by publisher mergers or the acquisition of publishers by other enterprises. They also examined the possibility of using document supply in lieu of renewing a package deal, but found that it would not be practical. Also, Jasper experienced problems with the Big Deal packages and consortial purchasing agreements when he was faced with a large budget cut. 24 He found one publisher that would allow the cancellation of some electronic journals, but, with another publisher, he would lose access to a large number of other titles and exclusion from the consortium. Other publishers limited cancellations to a stated percentage each year. Jasper noted that the complexity of online subscriptions combined with print subscriptions and of package deals arranged directly with vendor and through the consortium made cancelling electronic journals difficult.

Edlin and Rubinfeld examined Big Deal agreements from a legal perspective. 25 The authors discussed the growth and make-up of Big Deals, their pricing ties to print subscriptions, the issues surrounding cancellations, the effect on the library budget, and potential antitrust issues. They also examined the economic effects of Big Deals on the publishing world and reflected on issues surrounding exclusion and monopoly.

In 2005 the Association of Research Libraries (ARL) surveyed its members about large publisher bundles. 26 The survey focused on the five largest publishers. The most common reason for purchasing bundles was that the content and access were a good return on investment. One feature of the licensing was a restriction on the cancellation of print titles. Some members reported they could cancel a small percentage while others reported bans on cancellations. “Libraries reported an average satisfaction rating of 3.4 (on a 5-point scale) for the pricing of their first contract with any given publisher” for Big Deals, with a slightly lower average for consecutive contracts. 27

Hiott and Beasley provided a similar view of the importance of consortia in their study of two public libraries. 28 Houston Public Library relied on access to electronic journals and databases provided through TexShare. Forsyth County Public Library similarly relied on GALILEO, a virtual library of licensed and online research sites offered by the State of Georgia Board of Regents. Both libraries relied on their consortium for license negotiations, access maintenance, and use statistics reporting.

From 2004 through 2007, budget challenges, vendor changes, and technological improvements also had a serious effect on many of the basic functions of acquisitions work. Approval plans became important again, not only to assure good selection within a subject area, but to bring efficiencies to the acquisitions work. Consortia began to show interest in shared collection development and acquisitions. With the move from print to online journals, major projects of print journal subscription cancellations were common.

Fenner took a comprehensive look at approval plans. 29 She noted that the efficiency of a plan depended upon the profile specifications and how well it was maintained to meet the library’s needs. A title-by-title selection plan could be used either to supplement approval plans or to replace approval plans. Brush compared the circulation of books purchased on the engineering approval plan to the circulation of books in the engineering collection as a whole to determine the efficiency of a profile or whether the approval plan should be replaced by individual book ordering. 30 Books ordered on the plan were more heavily used, which warranted maintaining the approval plan. The data also revealed that electrical engineering books were not being ordered through the approval plan. The profile was adjusted to include them.

Boudewyns saw the use of approval plans for art as a way to free the art librarian for the significant amount of effort needed to support the acquisition of licensable digital image collection (LDIC). 31 She described LDICs as interactive systems that provided a mechanism for using digital images to create presentations and teaching materials. Lorenzen used her experience in developing an academic library art collection to illustrate the many changes in acquisitions due to new material formats and technological developments. 32 She described changes to the information needs and research practices of art students as they move beyond print to embrace the new digital technologies. Lorenzen also discussed recent changes to academic library acquisitions, such as the shift to digital formats, new approval plans that allow for ordering online, a focus on aggregator databases as an acquisitions source, and the effect of price increases on the budget.

Because of price and unfavorable currency exchange rates, Kamada utilized a slip selection approval plan profiled on Japanese language and linguistics to acquire resources for Japanese studies. 33 This plan allowed Kamada to stay within budget and spread the selection and ordering more evenly throughout the year. The slip selection plan was implemented for Japanese Buddhism and may be viable for small subject collections.

Curl and Zeoli described a consortial shared approval plan that was developed through a partnership with YBP for the Colleges of Ohio Networked System Online for Research and Teaching (CONSORT), which consists of Denison University, Kenyon College, Ohio Wesleyan University, and The College of Wooster. 34 The goal of the project was to develop a broad collection with less duplication while each college maintained its core collection. They were able to make broad use of the geographic and interdisciplinary tags supplied by the vendor for Asian and African material. Responsibility for various subject areas was shared between the CONSORT institutions on the basis of interest expressed. Fund codes were used to map responsibilities and institutions so that a shared YBP account could be established.

As a way to select vendors for the library’s book approval plans, Horava established a concurrent book approval pilot project for analyzing the performance of selected vendors of choice rather than sending a request for a proposal. 35 The vendors were reviewed on the same criteria applied to different subject disciplines. Mueller used a pilot approval plan as a way to move faculty from title-by-title selection to using approval plans. 36 The goals of the pilot were to free the faculty from selecting mainstream materials and allow more time for selecting unique materials.

Dali and Dilevko examined how Slavic and East European print materials were acquired by North American public and academic libraries. 37 They noted that many libraries used approval plans for Slavic collections, and many also acquired these materials through other means, such as book stores, book fairs, buying trips, exchanges, and gifts. Dali and Dilevko found that 51.4 percent of the surveyed libraries did not use approval plans.

As a way of augmenting traditional subject analysis, Mortimore applied the concept of “just-in-time” to acquisitions. 38 By combining interlibrary loan (ILL) data and circulation data by subject area, he determined which areas needed further development. Books were purchased rather than borrowed for these areas. The author proposed that just-in-time acquisitions often cost less than traditional ILL and contributed valuable items, which circulated frequently, to the collection.

With ongoing budget cuts or the need to fund electronic access, Gallagher, Bauer, and Dollar were faced with canceling some of their print titles. 39 Employing an evidence-based librarianship approach, they included data from a current periodical use study, SFX (Ex Libris’ link resolver) statistics, photocopying statistics, bound journal shelving statistics, gate counts, and relevant statistics from several library associations to make the best decisions. Although no two data sets correlated directly, the results of their analyses were quite similar. The authors also noted similarities in the journal titles used most frequently and that a significant portion of the print collection was never used during the study. They concluded with a discussion of the complexities of canceling print subscriptions due to pricing models or contractual obligations to retain print.

Carey, Elfstrand, and Hijleh also used an evidence-based approach on a cancellation project to reduce journal expenditures by 15 percent. 40 Their goals were to minimize the effect on the collection and gain support from faculty by including a bibliographer from each department who determined the journals to be cancelled. The bibliographers were provided with the average cost of use over a two-year period. Accounting reports were generated on the progress made toward reaching the goal. A project management system, CORE Project Management, was used to help manage the project.

Farrell and Truitt addressed a common problem faced by acquisition librarians—the need to build and maintain complex vendor records within the acquisitions module of their ILS. 41 Their article received the 2004 Association for Library Collections and Technical Services Blackwell Scholarship Award. The authors examined the creation and content of the vendor record as an example of the need to standardize vendor-supplied acquisitions records. By analyzing the data needed to support acquisitions activities and tasks, key data elements needed in the vendor record were identified and the difficulty in keeping that data current was noted. The goal of the article was to encourage the development of electronic data interchange (EDI) standards by which vendors would supply information about themselves to their library customers.

Laskowski was concerned about the consequences of new technology and the availability of various media formats on the acquisitions process. 42 She described common problems such as determining the appropriate format to acquire, complex and confusing pricing schemes, the assurance of quality for long-term preservation, and the need to purchase compatible playback equipment.

Chapman’s revised edition, Managing Acquisitions in Library and Information Services , is written primarily for library and information science students but is also a good resource for those new to acquisitions. 43 In this thin volume, Chapman covers the range of acquisition processes and online services.

The Internet allowed booksellers, serial agents, and publishers to move their work online. Print catalogs disappeared as the online databases were more complete and current. Ordering systems moved online as did much of customer support. New Internet providers became serious competition to traditional library vendors. The inclusion of “Books and the Internet: Buying, Selling, and Libraries” as a theme at the 2004 Charleston Conference was indicative of the importance of the topic. 44

Because the acquisition of out-of-print materials can be problematic and time consuming, Amsberry trialed outsourcing, which is the the searching, purchasing, and cataloging of out-of-print materials to a vendor. 45 The trial resulted in a high fulfillment rate, and the books received were in good condition, but receipt was slow compared to direct order from an online vendor. The cost per book was higher than if the book was ordered directly from an online vendor, but this increase was offset by savings in staff time. For libraries with small staffs, the results indicated that outsourcing could be a good alternative.

Holley and Ankem performed a comprehensive study on the effect of the Internet on the out-of-print book market. 46 They examined whether Internet use improved the availability of books that booksellers had difficulty finding in prior years and whether Internet use led to price decreases. The results showed a high availability of items and a significant decline in prices. Holley and Ankem found that the distinction between in-print and out-of-print disappeared in terms of availability, out-of-print materials often cost less than when the items were first published, the purchase of monographs might be a viable substitute for ILL, and retrospective collections could be built more easily than in the past.

While studies have examined the availability of out-of-print materials, Levine-Clark examined online booksellers for purchasing in-print materials. 47 The author found that Amazon had more books available than either Abebooks or Alibris. Abebooks, however, offered the highest average discount, followed by Amazon and Alibris. The time from publication affected pricing or availability very little. Because of the efficiency of acquisition through approval plans, the author did not consider Amazon as a replacement method for that process. However, ordering from online booksellers was feasible for second or replacement copies or titles shipped on approval plans.

Orkiszewski tested Amazon as a possible library vendor. 48 He found that not all items were discounted by Amazon and that discounts varied over time. If all the books in the study had been ordered from Amazon, the total cost would have been higher. The study revealed that the library vendors could compete with Amazon’s prices and provided services at a good value.

Lubiana and Gammon examined the European bookselling market and the movement toward electronic commerce. 49 They discussed book pricing and costs; availability; services (e.g., databases, online ordering and tracking, and online invoices); standards for payment transactions, such as EDI and Book Industry Standards and Communication; and sources for book acquisition.

The Guide to Out-of Print Materials by Tafuri, Seaberg, and Handman is an excellent resource for acquiring out-of-print materials of different types and serves as a quick reference resource. 50 The authors cover traditional methods of obtaining the materials as well as Internet resources.

Because budgets were shrinking, Lam stressed the need for a vendor-assessment system to determine which vendors offer the best quality and pricing. 51 She discussed how to establish a system and stressed that it should be comprehensive but user-friendly. The program should interface with the local library system to collect data and create spreadsheets for use in reporting key measurements. Gagnon looked at vendor relationships from a public library perspective. 52 He believed the key to successful library projects was a good relationship with vendors. While Gagnon considered the library’s relationship with the vendor as an investment, he noted that vendors must take the time to understand the needs and issues of the library.

Moghaddam and Moballeghi analyzed a variety of digital content aggregators and placed them into three categories: content hosts such as Ovid and Highwire Press, gateways such as SwetsNet and Biosis, and full-text content providers such as ProQuest and EBSCO. 53 The authors described important advantages and disadvantages to using aggregator services in acquisitions. They stressed that as new types of aggregators evolve, librarians need to understand their roles in the electronic resources supply chain.

Two important sources focus on vendors and acquisitions. Much of Anderson’s book, Buying and Contracting for Resources and Services: A How-To-Do-It Manual for Librarians , addresses vendor and good customer relationships. 54 The book also covers negotiating terms of service, license agreements, and the basics of approval plans. Ball’s book, Managing Suppliers and Partners for the Academic Library , covers vendor relationships and outsourcing, but the examples are limited to British libraries. 55

Flowers’ article described the key points to consider in negotiations for different types of library materials. 56 She discussed implications for process differences, such as one-time rather than ongoing purchasing, the volume and nature of orders placed, and the type of vendor and how they do business. Flowers provided solid definitions for the different issues to be negotiated depending on the acquisition method.

The ARL tracked member expenditures on electronic resources between 1994–5 and 2001–2. 57 During that timeframe, expenditures for electronic resources grew by nearly 400 percent while total materials expenditures increased by only 61 percent. In another ARL report, Johnson and Luther examined libraries’ moves to electronic-only journals. 58 They identified the need to control cost and the growing need for new content as two forces driving libraries to switch to electronic journals, which have resulted in an increase in discontinuing corresponding print editions. In a 2004–5 survey, the average ARL library spent 37 percent of its materials budget on electronic materials; some spent more than 50 percent. 59 Prabha analyzed journal subscription and format data for 2002–6. 60 She found that 5 percent of the subscriptions were available solely in electronic format in 2002. By 2006, 36 percent of journals were published solely in electronic format. Findings revealed that print subscriptions were canceled to move to online format to avoid a budget shortfall.

Eells studied the possible effects of a library’s decision to eliminate print journals in favor of electronic access. 61 She provided a substantial background on the primary methods of electronic journal publication, subscription options, and pricing models. Eells summarized several major publishers’ approach to the relationship between publishing costs and subscription pricing. Wolf described common issues faced when moving from print to electronic-only subscriptions. 62 Using a case study of the acquisition processes at Cardiff University, he described the challenges of dealing with a wide range of different subscription models, including consortium options and publishers’ Big Deals. Wolf outlined the steps needed to investigate these options and described how difficult and time-consuming that can be for acquisitions staff. He also discussed the challenges of managing the subscriptions over time.

Silberer and Bass discussed the effect of e-books on the ordering process. 63 In outlining the various ordering options, purchasing models, and distribution methods, the authors noted “there is no single source, option or strategy that is uniform for eBooks.” 64 An extensive chart compared offerings and services of twelve popular e-book providers. The authors described the role of the serial agent in selling subscriptions to collections of e-books, whether by lease or by access on a permanent basis. Their description of the current digital rights management technology for e-books demonstrated the complexity of acquisition options. Mikkonen also discussed e-book purchase models for consortia. 64 The pricing models for purchasing single e-books were similar to the models for purchasing printed books. However, if the e-book was purchased as part of a collection, the price might have been higher depending on the number of simultaneous users. Other pricing options were based on a one-time purchase or ongoing access. She suggested that consortium acquisitions should be based on the simplest pricing model because complicated negotiations and managing the different pricings could easily nullify the savings. In examining licensing, Mikkonen found that the e-book agreements needed to be adapted to include perpetual access rights.

Conger’s book, Collaborative Electronic Resource Management: From Acquisitions to Assessment , covers key topics associated with electronic resources. 66 Chapters 4 and 6 focus on budgeting, negotiating, and licensing.

Electronic resource management (ERM) was a major topic of concern during this review period. With increased acquisitions of electronic resources and the need to license them as part of the purchase process came the need to manage all the details of pricing, licensing, and access. Initially, libraries developed their own local version of an ERM system, and commercial systems followed later.

Stefancu, Bloss, and Lambrecht described the manual methods used for ERM at the University of Illinois at Chicago Library and the development of a sophisticated ERM system called the Database of Library Licensed Electronic Resources (DOLLeR). 67 DOLLeR was designed to provide access to license agreements, a Web e-mail gateway, and reporting capabilities. The use of tables for provider, license, resource, subscription data, and information provided by Serials Solutions were central to the design of the database.

North Carolina State University Libraries also designed their own ERM system, E-Matrix. 68 Raschke and Goldsmith stated that the initial plan was to develop E-Matrix to manage databases, aggregated resources, and electronic journal packages. However, because their ILS could not effectively manage print or electronic subscriptions, the ERM system was expanded to handle them. Kennedy examined the development of locally developed ERM systems at MIT Libraries, Pennsylvania State University Libraries, and UCLA Libraries, and their reasons for developing them. 69

Grover and Fons described Innovative’s partnership with several academic libraries to develop a system that met their needs and that could be integrated into the local library system or function as a standalone system. 70 Galloway discussed the development, implementation, and features of the Innovative ERM module at Glasgow University. 71 Tull described the conversion from the local management database to the Innovative ERM module at Ohio State University. 72 Tull et al. discussed the integrated features of the ERM module and the use of the three new types of records (resource, license, and contact) for managing electronic resources. 73

The final report of the Digital Library Federation Electronic Resource Management Initiative (DLF ERMI) was released in August 2004. 74 The document outlined ERM system needs, covering how groups of data elements are related and relating them to functional requirements. The document served as a standard for use by both libraries and vendors. Fons and Jewell summarized the key findings of the 2004 DLF ERMI report as background for proposing an ERMI II. 75 Several key library systems vendors developed electronic resource management systems on the basis of initial DLF ERMI specifications and modular components of their existing ILSs. According to the authors, ERMI II would move the standardization efforts further into the tracking of license data, the development of the license expression specification, the use of Project COUNTER Codes of Practice to standardize use data reports, and finally a standardized method of collecting use statistics from a variety of vendors known as SUSHI (Standardized Usage Statistics Harvesting Initiative). They concluded by recounting the key benefits implementing an original ERM system brought to the acquisitions function and by proposing additional functions needed to effectively manage electronic resources.

Managing Electronic Resources: Contemporary Problems and Emerging Issues , edited by Bluh and Hepfer, is an important collection of eleven papers from knowledgeable authors on a variety of ERM issues. 76 Many of the papers were presented at the 2003 and 2004 ALCTS Midwinter Meeting symposia.

Purchasing electronic resources often included a license agreement defining what the library and authorized users may do. The license agreements varied in complexity and often required a negotiation of terms. As libraries switch from print to electronic journals and books, librarians could be faced with more licenses to process.

Algenio and Thompson-Young examined the content of license agreements for e-books with a particular focus on how these contracts should be reviewed, revised, and negotiated to meet libraries’ needs. 77 They noted that while the one e-book, one user model can be easily negotiated to meet library requirements, license agreements for subscriptions to e-books were similar to those for e-journal packages. The authors recommended that libraries insert language into the license as needed to meet library requirements, and they described specific clauses and terms that should be considered important to any e-book license agreement.

The concept of creating and using a model license was thoroughly examined by Bosch in an article that covered the history and development of model licenses. 78 The article addressed the many benefits of using the model license from both the publishers’ and the libraries’ perspective. Bosch also pointed out the potential problems caused during negotiations by the use of the model license. The article provided a summary and explanation of the common elements found in most model licenses.

Chou and Zhou examined licensing from a legal perspective. 79 The article defined the types of legal protection provided to producers of digital content, described the purpose and types of license agreements, and discussed the effect of these agreements on libraries’ core values.

Through the use of a fictitious case study, Shipe discussed the barriers encountered in acquiring access to electronic database products. 80 The license agreement for his fictitious product included typical terms that were unacceptable for a state university: no access for the general public within the library, a clause indemnifying the licensor against any third-party legal action, and legal jurisdiction in another state. Shipe described the process of negotiating the license agreement with members of a society dependent on outside counsel, working with very busy university attorneys, and explaining the delay in access to their patrons.

Stemper and Barribeau identified perpetual access to e-journal content as a key problem for research libraries in an article that received the 2007 Best of LRTS Award. 81 Looking for license terms that provided useful guarantees of ongoing access should the subscription be canceled, the authors found that 36 percent of commercial publishers and 28 percent of society publishers provided perpetual access. If licenses were accepted without a perpetual access clause, libraries risked losing future access if a subscription is canceled. The authors concluded that academic libraries should insist on perpetual access even if it requires an additional fee.

Wiley surveyed thirteen large research libraries in the Midwest regarding ILL clauses in licenses. 82 The author noted that due to budget cuts many print journals were being cancelled without the realization that licenses for the electronic materials may prohibit or limit ILL. She presented specific examples of license terms that authorize and those that deny ILL uses. Wiley also discussed important issues affecting ILL services, such as copyright, the Commission on New Technological Uses guidelines, model licenses, and the power of consortium negotiation.

A key resource on licensing and acquisitions is A Guide to Licensing and Acquiring Electronic Information by Bosch, Promis, and Sugnet, with contributions by Davis. 83 Much of the text is focused on licensing electronic resources. The appendixes provide information on nonnegotiable and negotiable licenses and licensing terms. Another important resource is Licensing in Libraries: Practical and Ethical Aspects by Rupp-Serrano. 84 This book offers basic information on licensing, gives examples, and provides a history of licensing. Durrant’s book, Negotiating Licenses for Digital Resources , focuses on the process of negotiating with publishers and suppliers for better license terms and prices and walks readers through the preparation process. 85 Another publication of interest is the report on licensing by Primary Research Group (PRG). 86 PRG surveyed libraries across the United States, Canada, the United Kingdom, and other countries about database licensing practices. Their report covers licensing terms and provides historical information on licensing.

Reorganization and workflow changes continued to be a major topic during the period of the literature review. Between the years 2000 and 2003, articles focused mainly on changes within work groups. However, some articles examined the workflow between work groups and the need to realign staff to provide more support for the acquisition of electronic resources.

Grahame and McAdam reported on an ARL survey in which 87 percent of the respondents indicated they were making organizational changes to support the processing and managing of electronic resources. 87 Workload (staffing levels) and the need for an ERM module were identified as future challenges.

Higa et al. undertook a major reorganization to address staffing needs for a digital environment, a problematic team approach, and the lack of a clear vision. 88 A taskforce collected data on which to base the restructuring. As a result of that data, new or modified departments were established. One of the new departments, Digital Infrastructure Research and Development, handled long-range planning and research. A second new department, Digital Access, had responsibility for the access to the collections. The third new department, Print Resource Management and Optimization, addressed book selection and processing, serials processing, binding, and shelving. The Acquisitions and Licensing Department was modified to handle all resource purchasing and manage the journal collection development.

Morris and Larson described the complex issues encountered as their corporate research library moved from acquiring print to leasing digital resources. 89 They found that the basic acquisition processes for electronic resources were much more complex, requiring the understanding of pricing models and the negotiation of licensing and access rights with societies, aggregators, and many publishers. The authors highlighted the need to update job descriptions and staff skills to function effectively in the digital environment.

Ohler addressed one of the most pressing issues in acquisitions management: how to successfully change the functions of a print serials unit to effectively manage electronic resources acquisition and maintenance. 90 Using an extensive literature review to illustrate her perspective, Ohler detailed the complexities and risks of redesigning staff responsibilities and tasks to meet the complex demands of processing electronic resources. Ohler’s emphasis on the challenge of organizational change further emphasized the importance of examining all library work in light of user needs.

Kulp and Rupp-Serrano surveyed twenty-four academic library members of the Greater Western Library Alliance regarding the selection, funding, and workflow coordination of electronic resources acquisition. 91 While the authors found broad common categorizations of patterns for selecting and funding electronic resources, coordinating the acquisition and processing tasks revealed a much less clear scenario. Perhaps because of a lack of standards and technology to support managing electronic resources, many of these libraries indicated that their workflows were expertise-based, relying on one or two individuals to manage the acquisitions process.

Fenner outlined key issues affecting technical services operations. 92 Increased user expectations for electronic resources; the complexity of acquiring and managing the emerging new electronic formats; training in the many systems required to acquire, process, and catalog these resources; limited budgets; and hiring freezes forced technical services librarians to reconsider their basic assumptions and alter their traditional workflows. Fenner discussed organizational restructuring as a solution for streamlining procedures and using staff more efficiently.

Youngman, through a process-flow analysis, found a more effective way of handling the increased ordering and processing of monographs late in the fiscal year with limited staff. 93 The process eliminated duplicated effort and other steps, resulting in a better workflow and more efficient use of staff time.

Fowler and Arcand performed a serial acquisitions time and cost study to determine if there were standard data elements that could be used for making management decisions, such as the reassignment of staff time to other tasks. 94 During the study, an increase in electronic resources resulted in the need to hire an electronic resources coordinator because of the complexity of licenses and time required to negotiate them. The study revealed the difficulty in controlling time and cost. It verified the need for standard data elements in acquisition records down to a granular level to reduce the time and effort needed to produce management reports.

Alexander and Williams described the results of using an accelerated improvement workshop for their technical services staff at Wichita State University. 95 The focus of the workshop was to reduce the processing time for monographic acquisitions. The results of the workshop were immediately beneficial—processing time for books from receipt to shelf was reduced by ten days. The authors suggested that other acquisitions workflows, such as approval book plans, vendor relations, and special projects, also could be improved by this method.

Hepfer, Davis, and Waters’ chapter in Perspectives on Serials in the Hybrid Environment addressed the effect of acquiring electronic resources on technical services units. 96 The authors studied the State University of New York to identify the need for additional support, training of staff, and implementing an ERM system.

Libraries are steadily shifting from print to electronic resources. User demand, new technology, and financial savings will continue to drive this change. New pricing models for e-journals and e-books will continue to emerge. As print resources diminish, workflows will continue to be changed and technical services departments will continue to restructure to support the new demands of the digital environment. As new forms of electronic resources appear, ERM systems and standards will continue to evolve to handle the growth and effect of electronic resources.

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Systematic literature review of gender equity and social inclusion in primary education for teachers in Tanzania: assessing status and future directions

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• Published: 13 August 2024
• Volume 3 , article number  122 , ( 2024 )

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• Henry Nkya 1 &
• Isack Kibona 2  

Gender equity and social inclusion (GESI) are crucial for creating inclusive and equitable educational environments in primary schools. This systematic literature review aimed to interpret and synthesize the findings of previous studies on GESI interventions and programs in primary schools in Tanzania, identified gaps in the knowledge, and provided recommendations for policy and practice. A systematic literature review search identified 22 relevant studies that met the inclusion criteria. The studies conducted between 2010 and 2021, and the sample sizes of participants were above 50. More than 50% of the studies were conducted in rural areas and used a quasi-experimental design. The interventions evaluation included teacher training, community engagement, and curriculum reform. The systematic literature review employed statistical methods to measure effect sizes and employed traditional univariate systematic literature review to synthesize the results. A table summarizing the literature that met the inclusion criteria was created to ensure transparency and clarity in the data coding process. The systematic literature review found a positive effect of GESI interventions on various outcomes, including improved academic performance, reduced gender-based violence, and increased social inclusion. However, variations in effect sizes and study designs across the studies were noted. Several gaps were identified, such as the lack of long-term follow-up and the need for more rigorous study designs. The implications of the findings for policy and practice in promoting GESI in primary schools in Tanzania were discussed, and recommendations for future research were provided. This systematic literature review highlighted the importance of addressing GESI in primary school education in Tanzania and underscored the critical role of teachers in promoting these values. It calls for targeted interventions, policy enhancements, and further research to bridge the gaps identified in the literature.

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1 Introduction

GESI are critical components of education that ensure equitable access to education for all individuals, regardless of their gender, socioeconomic status, ethnicity, or other backgrounds. In Tanzania, GESI has become a significant concern, particularly in primary schools, where gender and social inequalities often lead to disparities in educational outcomes.

Research has shown that girls are more likely to face barriers in education than boys, including poverty, early marriages, and cultural bias that prioritize boys’ education over girls [ 28 ]. Furthermore, children from marginalized groups, such as children with disabilities, children from ethnic minority groups, and children from low-income families, often experience unequal access to quality education [ 38 ].

Addressing GESI issues in primary schools is crucial for ensuring that all children have access to quality education, which is essential for their personal development and future success. GESI initiatives can promote equity and inclusion in schools and create an environment where all children feel valued and supported [ 13 ].

Addressing gender stereotypes in teacher education programs can play a vital role in promoting GESI in primary schools [ 32 ]. Similarly, Okkolin et al. [ 27 ] suggest that interventions that address GESI can improve educational outcomes for girls and marginalized groups.

Overall, promoting GESI in primary schools is essential for creating a more equitable and inclusive education system that benefits all children [ 2 ]. It requires a concerted effort from policymakers, educators, parents, and communities to work together to create a learning environment that is supportive, respectful, and inclusive for all children.

1.1 Theoretical framework

This study is guided by the Social Justice Theory, which emphasizes the need for equitable treatment, opportunities, and outcomes for all individuals, particularly those from marginalized and disadvantaged backgrounds [ 10 ]. This framework is crucial in understanding the components of GESI and their impact on educational outcomes. The Social Justice Theory aligns with the goals of GESI by promoting fairness and the elimination of disparities in education [ 1 ].

1.1.1 Components of GESI

The key components of GESI in this study include [ 24 ]:

Gender equity: ensuring that girls and boys have equal access to education and opportunities.

Social inclusion: creating an inclusive environment where all students, regardless of their backgrounds, can participate and succeed.

Teacher training: educating teachers on gender-sensitive and inclusive teaching practices.

Community engagement: involving communities in promoting GESI.

Curricula reform: developing and implementing curricula that address GESI issues.

1.2 Justification for focusing on Tanzania

Tanzania provides a unique context for examining GESI due to its diverse population and the significant challenges it faces in achieving GESI in education [ 18 ]. Despite efforts to promote GESI, disparities persist, making it an important area of study to identify effective interventions and inform policy and practice.

1.3 Rationale for conducting a systematic literature review

A Systematic literature review is an essential tool for synthesizing research findings from different studies and summarizing the overall effect size of an intervention or variable of interest [ 34 ]. Conducting a systematic literature review on GESI in primary school education is critical for providing an overview of the existing research and identifying gaps that need to be addressed in future research. It also helps establish the overall effect of interventions aimed at promoting GESI in primary schools in Tanzania [ 9 ]. The results of the Systematic literature review can inform policies and practices aimed at promoting GESI in primary school education, thereby improving learning outcomes for all children, regardless of their gender, social, and economic backgrounds.

By addressing the GESI issues and synthesizing the existing literature, this systematic literature review aims to contribute to a more equitable and inclusive educational environment in Tanzania [ 22 ].

1.4 Research objectives

To identify the state of GESI in primary schools. This objective aims to provide a comprehensive understanding of how GESI issues manifest in primary schools, considering various social and educational contexts.

To number factors that contribute to gender GESI in primary schools. This shall allow informed decisions on the effort to contain the issues of GESI.

To synthesize the findings of previous studies on GESI in primary schools. This objective focuses on aggregating and interpreting the results of existing research to offer a clear and cohesive picture of what is known about GESI interventions and their effectiveness.

To identify gaps in the knowledge of GESI in primary schools. By evaluating the existing literature, this objective seeks to highlight areas where further research is needed, identifying shortcomings in study designs, populations, or intervention strategies.

To provide recommendations for improving GESI in primary schools. Based on the synthesis of previous studies and identified gaps, this objective aims to propose actionable strategies and policies to enhance GESI in primary education.

2 Methodology

Having set the study objectives, the search-strategy for the study involved conducting a comprehensive literature review of studies on GESI in primary schools. The search was conducted using electronic databases such as Google Scholar, JSTOR, and EBSCOhost. The search terms used were “gender equity,” “social inclusion,” “primary schools,” “Tanzania,” and “teachers.” Additionally, hand searching was conducted by reviewing the reference lists of identified studies to identify any relevant studies that may have been missed during the initial search.

Inclusion criteria:

The study must be conducted in primary schools.

The study must focus on gender equity and/or social inclusion in education.

The study must involve teachers as the primary participants or focus on the teacher’s role in promoting GESI.

The study must be published in English between 2010 and 2022.

Exclusion criteria:

Studies conducted outside Tanzania.

Studies not related to gender equity and/or social inclusion in education.

Studies not involving teachers or not focusing on the teacher’s role in promoting GESI.

Studies published before 2010 or after 2022.

The search process was conducted by two independent reviewers to ensure the accuracy and completeness of the search results. The reviewers screened the titles and abstracts of the identified studies for relevance and then reviewed the full text of potentially relevant studies. Any discrepancies between the reviewers were resolved through discussion and consensus. Reviewers made necessary steps to ensure a justified systematic review. Overall, the Authors reviewed 22 papers considered to have met the set criteria.

2.1 Choice of the effect size measure and analytical methods

The effect size measure used in this study was generated by statistical tools, making it suitable for systematics review that synthesize findings across multiple studies. For similar research questions, the study employed traditional univariate meta-analysis. This method was chosen because it is suitable for synthesizing the results of multiple studies that investigate similar research questions. Traditional univariate meta-analysis allows for the calculation of an overall effect size, providing a comprehensive summary of the impact of GESI interventions across different studies.

2.2 Choice of software

We used R software, specifically the ‘metafor’ package, for our analysis. This software was selected due to its robustness and versatility in conducting analytical procedures. The ‘metafor’ package supports a wide range of meta-analytic models and methods, making it a comprehensive tool for this type of analysis.

2.3 Coding of effect sizes

Table 1 summarizes the literature included that meets the inclusion criteria. This table includes information such as study design, sample size, effect sizes, and any other relevant variables. This step ensures transparency and clarity in the data coding process.

3 Results and analysis

The layout of the manuscript has been organized accordingly, so that headings and subheadings clearly demarcates each step of the systematic literature review process.

3.1 Status of GESI in primary schools in Tanzania

3.1.1 persistent gender disparities.

One of the major findings in this study was that gender disparities in primary education persist in Tanzania. This was evident in the lower enrollment and completion rates for girls in primary schools compared to boys [ 36 ]. Girls are less likely to attend school than boys, with enrollment rates lower for girls at both the primary and secondary levels. Additionally, girls are more likely to drop out of school due to various reasons, including early marriage, household responsibilities, and financial constraints [ 5 ]. These disparities highlight the ongoing challenges faced by girls in accessing and completing primary education.

3.1.2 Cultural and societal beliefs

Several studies have identified cultural and societal beliefs as a major factor contributing to gender disparities in primary education. In many Tanzanian communities, girls are expected to prioritize domestic responsibilities over their education, which can lead to low enrollment rates and high drop-out rates [ 39 ]. Furthermore, gender-based violence and sexual harassment are prevalent in schools, with girls facing discrimination and harassment from both male students and teachers [ 4 ]. These issues underscore the need for targeted interventions to create a safer and more supportive educational environment for girls.

Furthermore, Losioki and Mdee [ 12 ] found that gender stereotypes perpetuated in teacher education programs in Tanzania, which can affect the ability of teachers to create a gender-equitable and socially inclusive classroom environment. Teachers may unconsciously reinforce gender stereotypes in the classroom, leading to further marginalization of girls and other vulnerable groups.

3.1.3 Underrepresented minorities

In addition, limited access to education for children with disabilities or those from low-income families and marginalized communities can perpetuate social inequalities in primary schools [ 30 ]. These students often face significant barriers, including inadequate school facilities, lack of appropriate learning materials, and insufficient support services, which hinder their educational progress.

3.2 Strategies addressing the challenge

Despite these challenges, there have been government efforts to improve GESI in primary schools. The government of Tanzania has committed to providing equal access to education for all children, regardless of gender, ethnicity, or socio-economic status. The government has implemented policies such as free primary education and affirmative action programs to promote equal access to education for all children, regardless of gender or social status [ 15 , 26 ]. These initiatives aim to reduce financial barriers to education and encourage the enrollment and retention of girls and children from marginalized groups. This includes initiatives such as the Tanzania Education Sector Development Plan (ESDP) and the Primary Education Development Program (PEDP) [ 6 , 16 ]. These programs aim to address systemic barriers in education and promote inclusive practices in schools. The government also is open to collaborate with external forces like international interventions, community development agencies and NGO to work toward enhancing GESI. Some Strategies Addressing GESI Challenges. For instance, projects that focus on community engagement and parental involvement have shown positive impacts in changing attitudes towards girls’ education and promoting inclusive practices [ 17 ].

3.2.1 International and community-based programs

In recent years, there have been an increase in programs and initiatives aimed at promoting GESI in primary education. For example, the “Let Girls Learn” program, launched by the US government in partnership with the Tanzanian government, aimed to increase access to education for girls and reduce gender disparities in education [ 7 ]. Similarly, the Tanzania Gender Networking Programme (TGNP) has been working to promote GESI in education through community mobilization, advocacy, and capacity building [ 14 ].

3.2.2 Interventions with recorded impact

Previous studies identified several approaches that have been successful in improving GESI in primary schools. Among others, at least two are discussed. One such approach is the use of gender-responsive pedagogy, which involves incorporating gender-sensitive teaching practices and materials into the classroom [ 17 ]. This method helps create a more inclusive learning environment that acknowledges and addresses the different needs of boys and girls. Another effective intervention is the provision of sanitary pads and menstrual hygiene education to girls, which has been shown to improve school attendance and reduce drop-out rates [ 35 ]. By addressing menstrual hygiene needs, schools can help ensure that girls do not miss out on education due to a lack of resources or stigma associated with menstruation.

3.2.3 Intervention recommendations

GESI are essential components of a quality education system, and there is a need to address the persistent gender disparities in primary education. While cultural and societal beliefs continue to be major barriers, efforts to improve GESI through government policies and initiatives, as well as community-based programs, showed promise. The use of gender-responsive pedagogy and the provision of menstrual hygiene education and supplies were promising approaches that showed positive results [ 21 ]. However, more research and investment are needed to ensure that all children have access to primary education. Continued collaboration between the government, NGOs, and communities is essential to sustain and expand these efforts, ensuring that all students can benefit from a supportive and equitable educational environment [ 29 ].

Overall, there is still much work to be done to ensure GESI in primary schools [ 33 ]. It will require continued efforts and collaboration from the government, educators, and communities to address cultural and traditional beliefs, promote teacher education that challenges gender stereotypes, and provide equal access to education for all children. Policymakers must prioritize the allocation of resources to support GESI initiatives and ensure that schools are equipped to meet the diverse needs of all students [ 3 ].

By addressing these systemic issues, Tanzania can make significant strides towards achieving an inclusive and equitable education system that benefits all children, irrespective of their gender or socioeconomic background. Continued research and monitoring are essential to evaluate the effectiveness of existing interventions and identify new strategies to overcome persistent challenges in promoting GESI in primary education [ 31 ].

3.2.4 Gaps in the knowledge about GESI in primary schools

While the literature have provided valuable insights into the state of GESI in primary schools in Tanzania, several gaps in the knowledge still need to be addressed.

One major gap is the lack of research on the experiences of marginalized groups, including children with disabilities and those from low-income households. Studies have shown that these groups face significant barriers to accessing education and are often excluded from educational opportunities. For example, a study by Mwaijande [ 20 ] found that children with disabilities faced challenges such as lack of access to assistive devices and negative attitudes from teachers and other students. Similarly, research by Pak et al. [ 30 ] and Thomas and Rugambwa [ 36 ] revealed that children from poor families often struggle to pay school fees and may not have access to basic learning materials.

Another gap in the Tanzanian knowledge is the lack of research on the experiences of female teachers in primary schools. While studies have examined gender stereotypes and biases among teacher education programs, Thomas and Rugambwa [ 36 ] stressed that there is limited research on the experiences of female teachers in the classroom. Research on female teachers could shed light on the ways in which gender intersects with other forms of marginalization, such as age and socioeconomic status.

Furthermore, there is a need for more research on effective interventions and strategies for promoting GESI in primary schools. While some studies have evaluated the impact of interventions such as teacher training programs [ 19 , 25 ] , more rigorous evaluations of these interventions are needed to determine their effectiveness and sustainability.

Additionally, there is a lack of longitudinal studies that follow the long-term impact of GESI interventions. Many studies focus on short-term outcomes, but understanding the lasting effects of interventions is crucial for developing sustainable policies and practices.

In summary, while previous research has provided valuable insights into GESI in primary schools, several gaps in the knowledge need to be addressed. Future research should focus on the experiences of marginalized groups, including children with disabilities and those from low-income households, as well as female teachers. Additionally, the study showed more need for more rigorous evaluations of interventions and strategies aimed at promoting GESI in primary schools. Longitudinal studies that assess the long-term impact of these interventions would also be beneficial.

3.3 Patterns observed across the studies

As observed in the study, there were some patterns and trends identified across the studies. Firstly, there was a consistent finding that gender disparities persist in primary schools, particularly in terms of access to education and academic achievement. Despite efforts to promote GESI, girls and marginalized groups continue to face significant barriers that hinder their educational progress.

Secondly, there was a growing recognition of the importance of addressing GESI in primary education, as evidenced by the increasing number of interventions and programs aimed at promoting these values. This trend indicates a positive shift towards acknowledging and addressing GESI issues within the education system.

Thirdly, the systematic literature review revealed that the role of teachers is critical in promoting GESI in primary schools. Teacher training and support are essential for equipping educators with the skills and knowledge needed to foster an inclusive and equitable learning environment. Studies consistently highlighted the need for gender-sensitive pedagogy and teacher professional development programs.

Finally, there were some gaps in the current knowledge base, particularly with regard to the long-term impact of interventions and the effectiveness of different approaches to promoting GESI in primary education. While some interventions showed promising results, more research was needed to determine their sustainability and broader applicability.

By addressing these gaps and building on the patterns observed across studies, future research could contribute to a more comprehensive understanding of GESI in primary schools and inform the development of policies and practices to promote equity and inclusion for all students.

To sum up, analysis revealed that GESI interventions have a positive effect on various outcomes such as academic performance, reduced gender-based violence, and increased social inclusion. However, variations in effect sizes and study designs were observed across the studies. The studies included in the systematic literature review used various designs, such as randomized controlled trials (RCTs) and quasi-experimental designs, which contributed to the diversity in effect sizes.

4 Discussion

GESI is a critical components of a better-quality education system over otherwise. In Tanzania, primary education is the foundation for future academic and professional success [ 23 ], making it essential to ensure that all students, regardless of gender or social status, have access to an inclusive and equitable education. Previous studies explored the state of GESI in primary schools and identified areas for improvement.

The findings of the study highlighted the state of GESI in primary schools. The analysis of some 10 included studies revealed that significant disparities in access to education and academic performance among genders persist, with girls being more disadvantaged. Additionally, children from marginalized backgrounds, such as those from low-income families or those with disabilities, face substantial barriers to education.

To sum up, the study suggests a holistic approach involving teachers, schools, communities, and policymakers. Thus, multifaceted approach is necessary to create a more inclusive and equitable education system. Therefore, Recommendations include:

Providing comprehensive teacher training on gender-sensitive teaching methods.

Implementing community-based initiatives to address social and cultural barriers.

Developing policies and programs prioritizing marginalized students’ needs.

4.1 Implications of the study

Overall, the systematic literature review provided important insights into the state of GESI in primary schools. While progress has been made, significant challenges remain. Continued efforts and investments are necessary to promote a more equitable and inclusive education system. Future research should address the identified gaps and build on the promising interventions highlighted in this study. Based on the evidence synthesized, it is clear that targeted interventions are necessary to address the barriers that girls and other marginalized groups face in accessing and completing primary education. The study has the following recommendations on policy and practice and the areas for future research.

4.1.1 Addressing school issues related to GESI

Teacher training: policies should mandate comprehensive training for teachers on gender-sensitive teaching practices. Educators need to be equipped with the skills and knowledge to foster an inclusive classroom environment that supports both boys and girls. This includes understanding how to address and counteract gender stereotypes and biases.

Providing resources: schools should be equipped with resources to support girls’ education. This includes the provision of sanitary pads, access to clean and safe gender-segregated toilets, and gender-sensitive teaching materials. These resources are essential in reducing barriers to attendance and participation for girls.

Reviewing curricula: the school curriculum should be reviewed and revised to promote GESI. Curricula should reflect the diversity of Tanzanian society and challenge existing gender stereotypes. Including content that promotes GESI will help inculcate these values in students from a young age.

4.1.2 Addressing structural and socio-economic barriers

Financial support: there should be policies to provide financial support to families who cannot afford school fees. This can include scholarships, free school meals, and other financial incentives that alleviate the economic burden on families and keep girls in school.

Cultural norms and attitudes: interventions must focus on changing cultural norms and attitudes that limit girls’ access to education. Community engagement and awareness campaigns are crucial in shifting perceptions and promoting the value of girls’ education. Programs should aim to involve parents and community leaders in promoting gender equity.

Reducing gender-based violence: schools should implement strict policies against gender-based violence and harassment. Providing a safe and supportive environment is crucial for retaining girls in school. Support services for victims of violence and harassment should be readily available.

4.1.3 Promoting girls’ participation and leadership

Extracurricular activities: schools should create opportunities for girls to engage in extracurricular activities. Programs such as sports, arts, and clubs can enhance girls’ skills and confidence, providing a platform for them to express themselves and develop leadership qualities.

Leadership training: providing leadership training for girls to support their involvement in decision-making processes within schools and communities is essential. This training can empower girls to take active roles in their schools and communities, fostering a sense of agency and leadership.

4.1.4 Comprehensive and integrated approach

Involving multiple stakeholders: a comprehensive approach to promoting GESI should involve multiple stakeholders, including the government, civil society, and communities. Collaboration among these groups is essential for creating a supportive environment for GESI.

Evidence-based interventions: policies and practices should be guided by evidence-based interventions tailored to the specific needs and contexts of different regions and populations. Utilizing data and research to inform practices ensures that efforts are effective and impactful.

Monitoring and evaluation: continuous monitoring and evaluation of interventions are necessary to assess their effectiveness and make necessary adjustments. This helps in ensuring the sustainability and scalability of successful initiatives.

The study highlights the importance of a comprehensive and integrated approach to promoting GESI in primary schools. It underscores the need for targeted interventions, policy enhancements, and continued efforts to address the persistent barriers that girls and marginalized groups face. By implementing these recommendations, Tanzania can make significant strides towards achieving a more inclusive and equitable education system for all children.

4.2 Areas for future research

Future research and policy efforts should focus on sustaining and scaling successful interventions, ensuring that all children, regardless of gender or socio-economic background, have access to quality education. Future research should address these gaps:

Experiences of marginalized groups: more high-quality research is needed on the experiences of marginalized groups, including children with disabilities and those from low-income households.

Female teachers: investigate the experiences of female teachers in primary schools to understand how gender intersects with other forms of marginalization, such as age and socioeconomic status.

Effectiveness of interventions: conduct more rigorous evaluations of specific interventions and strategies for promoting GESI, including long-term impact studies.

Intersectionality: explore the intersectionality of factors such as gender, socioeconomic status, and ethnicity to provide a more comprehensive

5 Conclusion

GESI is crucial for improving access to education, ensuring equal opportunities, and promoting positive social outcomes. Teachers play a critical role in promoting these values and must receive appropriate training and support to create inclusive learning environments. Policymakers and education leaders must prioritize efforts to address GESI in primary schools, including investing in research to understand the factors contributing to gender and social equality and identifying effective strategies for promoting GESI.

The systematic literature review examined the state of GESI in primary schools and revealed significant challenges, particularly in terms of teacher training and the implementation of policies and programs. The review highlighted persistent gender disparities and the barriers faced by marginalized groups, such as children with disabilities and those from low-income families.

The findings suggest that targeted interventions are needed to address these barriers, recommended interventions include:

Increasing access to education: efforts to increase access to education for marginalized groups, such as scholarships and school feeding programs.

Policy development: implementing policies that address gender-based violence and discrimination.

Community engagement: involving multiple stakeholders, including government, civil society, and communities, in promoting GESI.

Develop and implement teacher training programs: focus on GESI principles, awareness of gender biases, strategies for promoting inclusivity, and the use of gender-sensitive teaching materials.

Develop and implement gender-sensitive curricula: address gender biases and stereotypes across all subject areas.

Strengthen policies and regulations: enforce policies that promote GESI in school governance, teacher recruitment, and student enrollment.

Increase participation of girls: provide incentives for girls to attend school, such as scholarships and school feeding programs, and improve school infrastructure.

The study provides crucial insights into the state of GESI in primary schools and underscores the need for coordinated and sustained efforts to address these challenges. By implementing the recommended strategies and involving all stakeholders, Tanzania can ensure that all children have access to quality primary education that promotes GESI.

Data availability

No datasets were generated or analysed during the current study.

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Nkya, H., Kibona, I. Systematic literature review of gender equity and social inclusion in primary education for teachers in Tanzania: assessing status and future directions. Discov Educ 3 , 122 (2024). https://doi.org/10.1007/s44217-024-00221-8

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Insights into the ANKRD11 variants and short-stature phenotype through literature review and ClinVar database search

• Dongye He   ORCID: orcid.org/0000-0001-6704-7354 1 , 2 ,
• Mei Zhang 1 , 3 ,
• Yanying Li 1 , 3 ,
• Fupeng Liu 1 , 2 &
• Bo Ban   ORCID: orcid.org/0000-0002-3950-1422 1 , 2 , 3  

Orphanet Journal of Rare Diseases volume  19 , Article number:  292 ( 2024 ) Cite this article

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Ankyrin repeat domain containing-protein 11 (ANKRD11), a transcriptional factor predominantly localized in the cell nucleus, plays a crucial role in the expression regulation of key genes by recruiting chromatin remodelers and interacting with specific transcriptional repressors or activators during numerous biological processes. Its pathogenic variants are strongly linked to the pathogenesis and progression of multisystem disorder known as KBG syndrome. With the widespread application of high-throughput DNA sequencing technologies in clinical medicine, numerous pathogenic variants in the ANKRD11 gene have been reported. Patients with KBG syndrome usually exhibit a broad phenotypic spectrum with a variable degree of severity, even if having identical variants. In addition to distinctive dental, craniofacial and neurodevelopmental abnormalities, patients often present with skeletal anomalies, particularly postnatal short stature. The relationship between ANKRD11 variants and short stature is not well-understood, with limited knowledge regarding its occurrence rate or underlying biological mechanism involved. This review aims to provide an updated analysis of the molecular spectrum associated with ANKRD11 variants, investigate the prevalence of the short stature among patients harboring these variants, evaluate the efficacy of recombinant human growth hormone in treating children with short stature and ANKRD11 variants, and explore the biological mechanisms underlying short stature from both scientific and clinical perspectives. Our investigation indicated that frameshift and nonsense were the most frequent types in 583 pathogenic or likely pathogenic variants identified in the ANKRD11 gene. Among the 245 KBGS patients with height data, approximately 50% displayed short stature. Most patients showed a positive response to rhGH therapy, although the number of patients receiving treatment was limited. ANKRD11 deficiency potentially disrupts longitudinal bone growth by affecting the orderly differentiation of growth plate chondrocytes. Our review offers crucial insights into the association between ANKRD11 variants and short stature and provides valuable guidance for precise clinical diagnosis and treatment of patients with KBG syndrome.

The ANKRD11 gene (OMIM#611192) is mapped to human chromosome 16q24.3 and encodes an ankyrin repeat domain-containing protein 11 that belongs to a member of the ankyrin repeats-containing cofactor family (ANCO). It is relatively conserved across species and ubiquitously expressed in multiple organs and tissues, particularly in the brain and ovary [ 1 , 2 ]. The ANKRD11 protein, consisting of 2,663 amino acid residues, structurally includes the ankyrin domain (ANK), transcriptional activation domain (AD), transcriptional repression domains (RD1 and RD2), and multiple putative nuclear localization signals (NLSs) [ 3 ]. The N-terminal ANK domain follows the canonical helix-loop-helix-β-hairpin/loop configuration and is comprised of five consecutive ankyrin repeat motifs. Each motif contains a 33-residue sequence and facilitates protein-protein interaction to coordinate subsequent transcriptional regulatory processes [ 4 , 5 , 6 ]. The ANKRD11 protein binds to the conserved N-terminal Per-Arnt-Sim (PAS) region of p160 coactivator via its ANK domain, concurrently, recruits histone deacetylases (HDACs) through its RD1 or RD2 domain. When p160 coactivator binds to the hydrophobic cleft within the C-terminal ligand-binding domain (LBD) of nuclear receptors (NRs) through its LXXLL motifs, the assembly of p160/ANKRD11/HDACs complex suppresses NRs-mediated ligand-dependent transactivation [ 7 ]. The ANKRD11 protein also interacts with the N-terminal 84 amino acids of ADA3 (alteration/deficiency in activation 3), which is an essential part of the p300/CBP [cAMP-response-element binding protein-binding protein]-associated factor (P/CAF) complex. This complex connects coactivators to histone acetylation and basal transcription machinery, resulting in the recruitment of the P/CAF complex and the specific regulation of ADA3 coactivator in a transcription factor-dependent manner [ 8 ]. Moreover, the ANKRD11 protein is capable of amplifying p53 activity through the enhancement of P/CAF-mediated acetylation [ 6 ]. Overall, the ANKRD11 protein, through its various functional domains, collectively facilitates the formation of a molecular bridge between coactivators or corepressors and histone deacetylases (HDACs) or histone acetyltransferases (HATs), thereby precisely regulating the transcription of target genes.

Initially, ANKRD11 has been recognized as a tumor suppressor gene in breast cancer due to its location within the chromosomal region 16q24.3, which is widely acknowledged for its frequent loss of heterozygosity (LOH) among patients suffering from breast cancer [ 9 , 10 ]. Under normal physiological conditions, the estrogen receptor (ER)/amplified in breast cancer 1 (AIB1)/ANKRD11/HDACs or transcriptional enhanced associate domain (TEAD)/yes-associated protein (YAP)/AIB1/ANKRD11 complex functions to suppress the transcriptional activation of oncogenes in breast cancer [ 11 , 12 ]. However, aberrant DNA methylation of three CpGs within a 19-base pair region of the ANKRD11 promoter leads to its down-regulation, thereby disrupting the assembly of the complex and consequently promoting breast tumorigenesis [ 13 ]. ANKRD11 haploinsufficiency was later identified in KBG syndrome (KBGS) patient-focused clinical and molecular studies, confirming the dominant pathogenic mechanism responsible for this condition (OMIM#148050). KBGS was initially reported by Herrmann and colleagues in 1975 and characterized by macrodontia of the upper central incisors, distinctive craniofacial findings, postnatal short stature, skeletal anomalies and, neurodevelopmental disorders, sometimes with seizures and electroencephalogram (EEG) abnormalities [ 14 , 15 , 16 ]. Patients harboring ANKRD11 pathogenic variants exhibit overlapping features between KBGS and Cornelia de Lange syndrome or Coffin-Siris-like syndrome, particularly neurological and skeletal anomalies [ 17 , 18 ]. KBGS typically presents with a wide range of phenotypic manifestations, each varying in severity [ 19 ]. The biological function and cellular mechanism of ANKRD11 variants associated with the KBGS features have garnered significant interest and attention within the academic community. Previous study has established the pivotal role of the ANKRD11 gene in proliferation, neurogenesis and neuronal localization of cortical neural precursor cells by utilizing a Yoda mice model harboring a point mutation within the ANKRD11-HDAC interaction region, and the underlying mechanism was linked to alterations in the acetylation patterns of specific lysine residues (H3K9, H4K5, H4K8, H4K16) on the target genes regulated by ANKRD11 [ 20 ]. Further investigation has revealed that ANKRD11 regulates pyramidal neuron migration and dendritic differentiation of mouse cerebral cortex through the coordination of P/CAF to facilitate the acetylation of both p53 and Histone H3, which subsequently leads to the activation of brain-derived neurotrophic factor (BDNF)/tyrosine receptor kinase B (TrkB) signaling pathway [ 21 ]. Moreover, Roth and their colleagues developed a heterozygous neural crest-specific ANKRD11-mutant mice model, and revealed that multiple ossification centers in the middle facial bone of mice failed to expand or fuse properly, leading to a significant delay in bone maturation and a severe restriction in bone remodeling [ 22 ]. Recent research has uncovered that conditional knockout of the ANKRD11 gene within murine embryonic neural crest leads to severe congenital cardiac malformations and the underlying mechanism was linked to a reduction in Sema3C expression levels, coupled with diminished mTOR and BMP signaling within the cardiac neural crest cells of the outflow tract [ 23 ]. Based on the accumulating evidence from ongoing research into gene functions, the relationship between ANKRD11 pathogenic variants and the clinical features of KBGS is better understood than ever before. However, the role of ANKRD11 variants in inducing short stature has not received sufficient attention, particularly regarding its frequency of occurrence and the underlying biological mechanisms of action.

Materials and methods

We investigated publicly available online resources including published literature in Web of Science, PubMed, Google Scholar, and Wanfang database by searching keywords “KBGS”, “ANKRD11”, “Short stature” and “Intellectual disability” as well as genetic testing records in ClinVar database between July 2011 and March 2024. In this review, we included a total of 78 published papers that encompassed cohort studies, case series or single-case reports, and gathered 583 ANKRD11 variants, which were classified as pathogenic or likely pathogenic according to the American College of Medical Genetics and Genomics (ACMG)-Association for Molecular Pathology (AMP) guideline (Supplemental material  1 ). Among these variants, 202 were reported in published papers and 381 were described in the ClinVar database. Certain large deletions or duplications of the ANKRD11 gene were not considered in this analysis, as the complexity of their impact on the amino acid sequence of the encoded protein posed challenges for interpretation. We have also excluded patients with 16q24.3 microdeletions, 16q24.3 microduplications and dual molecular diagnosis involving ANKRD11 and/or flanking genes, as the role of other genes in contributing to the height phenotype remains uncertain. Furthermore, hotspot variants within ANKRD11 were analyzed in 838 patients, comprising 457 derived from the literature and 381 derived from the ClinVar database (Supplemental material  2 ). ANKRD11 allele frequency below 1% in the general poulation was obtained from gnomAD ( http://gnomad-sg.org/ ). 245 patients were reported to have height data, of which 112 had a height SDS. The differences in height SDS among patients with short stature carrying various ANKRD11 variants were further analyzed (Supplemental material  3 ). Data was described as mean ± SDS, and analyzed with one-way analysis of variance (ANOVA) followed by Tukey’s multiple comparisons test. A significant difference was considered when the p -value was less than 0.05.

Molecular spectrum of ANKRD11 variants

Since ANKRD11 was identified as the causal gene for KBGS in 2011, more than 340 KBGS patients have been reported worldwide [ 24 ]. Considering the variant data documented in the ClinVar database, it is projected that the number of patients with ANKRD11 variants exceeds 800. Despite the global prevalence of KBGS worldwide remaining unknown, its prevalence is underestimated due to a limited understanding of the disease phenotype and molecular underpinning. Consequently, establishing the spectrum of genetic variation in the ANKRD11 gene holds the promise of not only enhancing our understanding of disease’s pathogenesis but also enabling clinicians to render a precise molecular diagnosis for KBGS. A total of 583 ANKRD11 variants encompassed nearly the entire sequence of amino acids [ 1 , 2 , 15 , 17 , 18 , 19 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 ] (Fig.  1 ). All identified ANKRD11 variants were present in a heterozygous state, aligning with early embryonic lethality of Yoda mice observed in homozygotes, as demonstrated by Barbaric et al. [ 3 ]. This review encapsulates the up-to-date molecular landscape of ANKRD11 variants, nevertheless, in light of the continual discovery of patients with newly identified ANKRD11 variants, it needs to be supplemented and updated in time.

Molecular spectrum of ANKRD11 variants. A total of 583 ANRKD11 (likely) pathogenic variants were collected through literature review and ClinVar database. ANKRD11 variants were shown by frameshift, nonsense, missense, splice and inframe deletion, respectively. ANK: ankyrin repeat domain, RD1: repression domain 1, AD: activation domain, RD2: repression domain 2

All ANKRD11 variants in the map were classified into five types: frameshift variants (340/583, 58.32%), nonsense variants (163/583, 27.96%), missense variants (54/583, 9.26%), splicing variants (21/583, 3.60%) and inframe deletion variants (5/583, 0.86%) (Fig.  2 ). Variants occurring in ANK, RD1, AD, RD2 and non-domain region accounted for 3.60%, 10.12%, 9.09%, 15.10% and 62.09% of the total variant pool, respectively (Fig.  2 ). Multiple putative NLSs within the interval between the RD1 and AD regions were categorized as part of the non-domain segment, primarily due to the absence of definitive and evidence-based localization data [ 3 , 5 , 15 , 48 ]. Specific variants occurring within these NLSs may impair the nuclear targeting of the ANKRD11 protein. Notably, the most common variants were frameshift and nonsense variants, which give rise to prematurely truncated forms of the ANKRD11 protein. 62.96% (34/54) of ANKRD11 missense variants were found to cluster within C-terminal RD2 region. The majority of these missense variants, particularly those impacting arginine residues, were reported to impair protein stability or transcriptional activity, however, they did not produce an obvious impact on the protein’s subcellular localization [ 61 , 66 ]. Additionally, alternative splicing events predominantly affected the C-terminal RD2 (13/21) and N-terminal region (8/21). It is not surprising that those affecting 5’ and 3’ splice sites are commonly implicated as the underlying cause of hereditary disorders [ 97 ]. Nonetheless, how these hypothesized splicing variants impact the encoded protein requires an in-depth examination of splicing patterns by cDNA analysis, and frequently involves a Mini-gene assay. Other types of ANKRD11 variants were relatively uncommon including p.Lys1347del, p.Thr2471_Gly2474del, p.Glu2524_Lys2525del, p.Q2350del, and p.R595_A2663delinsS. Interestingly, p.Lys1347del has been demonstrated to significantly disrupt the transcriptional activation of downstream p21 gene but did not influence the levels of ANKRD11 mRNA or protein [ 2 , 15 , 19 , 61 ]. Theoretically, protein-truncating variants (PTVs) cause a more detrimental effect on protein function compared to the consequences of amino acid deletions (≥ 1) and single amino acid substitution [ 98 , 99 ]. The impact of various types of genetic variants on the ANKRD11 protein function requires further investigation by a range of functional analyses.

The percentage of different types of ANKRD11 variants located in different functional domains. The pie chart indicates the percentage of variants within different domains. 10 X 10 dot plot represents the percentage of different variant types. The column shows the the proportion of five mutation types within different domains of ANKRD11. ANK: ankyrin repeat domain, RD1: repression domain 1, AD: activation domain, RD2: repression domain 2

Hotspot variants of ANKRD11 protein

Mutation rates vary significantly along nucleotide sequences such that variants often concentrate at certain positions called hotspots [ 100 ]. DNA sequences prone to variation are highly dependent of gene sequence and structure as well as its chromosomal location, such as GC-rich region, microsatellites, meiotic recombination, nonallelic homologous recombination, centromeric rearrangements, telomeres and subtelomeric regions, replication timing and common fragile sites [ 101 , 102 ]. Therefore, hotspot variants are indicative of the structural and functional properties of DNA sequence. Within the spectrum of ANKRD11 variants, over two dozen distinct variants have been identified in at least three patients. Beyond a few variants that have been vertically inherited within a single family, the majority of variants were discovered in multiple sporadic patients, underscoring the propensity for these genetic variants to arise independently in unrelated individuals. Four hotspot variants of ANKRD11 protein were observed including p.Glu461Glnfs*48, p.Lys635Glnfs*26, p.Glu800Asnfs*62 and p.Lys803Argfs*5 (Fig.  3 A). These four variants are frameshift variants generated by c.1381_1384delGAAA, c.1903_1907delAAACA, c.2395_2398delAAAG and c.2408_2412delAAAAA, respectively. Two additional prevalent frameshift variants were traced back to analogous genomic alterations including p.Asn725Lysfs*23 and p.Thr462Lysfs*47 arising from c.2175_2178delCAAA and c.1385_1388delCAAA, respectively. The propensity for short deletions within AAA-type-containing sequences may be associated with polymerase slippage events induced by tandem repeats, a well-established mechanism for indels [ 100 ]. Nonetheless, it should be highlighted that CCC-type-containing sequences exhibit a heightened vulnerability to this form of genetic variation [ 103 , 104 ]. RD2 domain located at the C-terminus of ANKRD11 seemed to be particularly vulnerable to a range of variant events in KBGS patients, with missense variants being notably prevalent (Fig.  3 A). Conversely, the missense variants occuring in RD2 domain were relatively rare in general population (Fig.  3 B). This was consistent with the results of in vitro cellular assays, which showed that missense variants occurring in the RD2 domain impaired the protein function of ANKRD11 [ 66 ]. Some frameshift and nonsense variants of ANKRD11 have been identified in general population, such as p.Glu2082Argfs*20, p.Ser2180Phefs*6, p.Glu1075* and p.Gln2507*, indicating a pattern of variable expressivity and incomplete penetrance associated with ANKRD11 variants [ 2 ]. Taken together, the presence of hotspot variants offers valuable insights into the inherent vulnerability of specific DNA sequence to abnormal DNA repair, replication, and modification or environmental exposures. These findings warrant in-depth exploration at the molecular level to unravel the underlying mechanisms and implications.

Frequency of ANKRD11 variants in a total of 838 KBGS patients ( A ) and ANKRD11 allele frequency in general population ( B ). ANKRD11 allele frequency below 1% in general poulation was obtained from gnomAD ( http://gnomad-sg.org/ ). The abscissa represents the full-length amino acid sequence of ANKRD11, and the ordinate represents the frequency

ANKRD11 variants and short stature in patients with KBGS

Frequency of occurrence of short stature in patients with ankrd11 variants.

Short stature is defined as height less than − 2 standard deviation (SD) or below the third percentile of corresponding mean height for age-, gender- and race-matched populations [ 105 , 106 ]. As widely recognized, height is a highly heritable characteristic, and is classically influenced by hundreds of common variants pinpointed by genome-wide association studies (GWAS) [ 107 , 108 ]. By comparison, the impact of rare and low-frequency monogenic variants on height is more pronounced, yielding a larger effect size compared to single nucleotide polymorphisms (SNPs) [ 109 , 110 ]. Finding new genes with rare deleterious variants relating to growth is of considerable significance. Case series and individual reports serve as valuable sources of evidence for investigating the frequency of occurrence of short stature among patients harboring ANKRD11 variants. In 121 patients reported with height SDS, a significant proportion, amounting to 48.76% (59/121), exhibited a height below the − 2 SDS (Fig.  4 A). This prevalence was observed with nearly equal frequency across genders, with female patients exhibiting a rate of 46.43% (26/56) and male patients exhibiting a rate of 49.02% (25/51). The height SDS of females and males were − 1.80 ± 1.27 and − 1.85 ± 1.28 SDS, respectively. Upon incorporating additional patients recorded with height percentile values into the analysis, the proportion of patients with short stature was found to be 47.35% (116/245). Moreover, while some patients did not exhibit short stature, their adult height SDS or growth percentile might be lower than expected if their genetic potential (mid-parental height) was taken into account. However, most studies did not report patients’ genetic potential for height, making it challenging to extract this specific information from the published literature. Overall, approximately half of the patients with ANKRD11 variants exhibited short stature, consequently, this characteristic stand as an important manifestation of KBGS attributable to ANKRD11 variants. Certainly, compared to other features, the incidence of short stature was less frequent than that of craniofacial anomalies (100%), dental anomalies (80%) and intellectual disability (77%) [ 48 ]. Notably, patients with ANKRD11 variants displayed a variable height phenotype ranging from as low as -4.9 SDS to as high as + 1.5 SDS. It can be ascribed to several factors, including genetic context of the gene, modified penetrance, variant type and variant location [ 111 , 112 ]. There was no significant difference in height SDS among patients with ANKRD11 variants located in different regions or with different ANKRD11 variant types ( p  > 0.05) (Fig.  4 B&C). Previous investigation has revealed that terminations close to the C-terminus of the ANKRD11 protein tended to have less severe short stature, but the research did not yield a statistically significant difference or a clear trend in the severity of short stature among the various types of ANKRD11 variants [ 39 ]. The findings of the current study indicated that no genotype-phenotype correlation was established. Certainly, a limited number of patients with ANKRD11 variants across different domains present a significant constraint on this conclusion.

Distribution of gender and height SDS of patients having ANKRD11 variants ( A ) and comparison of height SDS of patients having ANKRD11 variants within different domain ( B ) or having different ANKRD11 variant types ( C ). ANK: ankyrin repeat domain, RD1: repression domain 1, AD: activation domain, RD2: repression domain 2

Frequency of ANKRD11 pathogenic variants in short-stature cohorts

Functional variants in the ANKRD11 gene have been identified through exome sequencing or gene panels in multiple short-stature cohorts (Table  1 ). The frequency of pathogenic variants was estimated to be between 0.35% and 0.55% [ 43 , 68 , 79 , 113 ]. These variants were identified in patients initially diagnosed as having syndromic short stature, however, subsequent molecular diagnosis facilitated a more precise diagnosis of KBG syndrome. Syndromic short stature represents a phenotypic and genetically heterogeneous disease, and it accounts for a large part of the etiology of short stature. Considering the wide range of phenotypic manifestations and variable degree of severity, certain patients with short stature suffering from KBGS may not be accurately diagnosed in clinical practice. Consequently, it is likely that these patients harbor rare pathogenic variants in the ANKRD11 gene, which may elude detection and result in their classification within the vast and enigmatic group of short stature with undetermined etiologies. Genetic testing should be factored into precise diagnosis of syndromic short stature in the future. Based on previous studies estimating the occurrence of short stature at approximately 3% [ 114 , 115 , 116 ], the prevalence of ANKRD11 variants in the general population could be roughly calculated to be in the range of 0.0105–0.0165%. Nevertheless, given the limited sample sizes and the variability among different cohorts studied for short stature, the frequency of ANKRD11 variants remains uncertain and requires a more accurate assessment. This evaluation should ideally be conducted through large-scale population screenings, employing artificial intelligence-enhanced phenotyping in conjunction with genetic testing [ 117 ]. Despite the growing awareness and attention this condition has recently garnered in the clinical and genetic research communities, there remains a significant gap in the identification and management of KBGS patients. Therefore, the development of international consensus guidelines for the diagnosis of KBGS is of paramount importance.

Recombinant human growth hormone therapy

In 1985, recombinant human growth hormone (rhGH) received approval from the US Food and Drug Administration (FDA) for the treatment of children with severe GHD. Since then, over the past nearly forty years, the application of rhGH has been progressively expanded to enhance the height outcomes in children with a variety of growth disorders, including chronic renal insufficiency (CRI), ISS, SGA without catch-up growth, Prader-Willi Syndrome (PWS), Noonan syndrome (NS), Turner syndrome (TS) and SHOX haploinsufficiency [ 118 , 119 ]. The advent of high-throughput sequencing technology has ushered in a period of rapid advancement in the field of genetics and genomics, and this progress has significantly broadened our capacity for diagnosing and treating conditions associated with short stature. We are now entering a transformative era characterized by molecular diagnosis and the tailoring of therapeutic interventions to the specific genetic makeup of individuals, including their responsiveness to rhGH therapy [ 120 ]. It has been observed that pathogenic variants in the aggrecan ( ACAN ), natriuretic peptide receptor 2 ( NPR2 ), and Indian hedgehog ( IHH ) genes, which are integral to growth plate development, have been consistently associated with a positive response to rhGH therapy [ 121 , 122 , 123 , 124 , 125 ]. In this review, we delineated the growth response observed in patients harboring ANKRD11 variants who received rhGH therapy (Table  2 ). The ages at initiation of rhGH treatment ranged from 5.2 to 14 years, and the treatment duration extended from 0.58 to 3 years. Following rhGH treatment, all patients exhibited varying levels of catch-up growth, as reflected by a range in Δ height SDS from 0.14 to 1.87. Among the nine patients, five showed a significant height improvement, reaching values above − 2 SDS ( -0.75 SDS for patient 3, − 0.7 SDS for patient 4, -1.86 SDS for patient 5, -1.8 SDS for patient 8 and − 1.91 SDS for patient 9). Most patients displayed either a good or moderate response to rhGH therapy. However, there was an exception with patient 3, a 7.9-year-old girl, whose height SDS only increased by 0.14 following a continuous treatment period of 0.58 years. Practically, a four-year-old girl form Australia with ANKRD11 variant (c.6472G > T, p.Glu2158*), showed no response to rhGH therapy [ 49 ]. The girl was not included in Table  2 due to the lack of height data. The potential existence of additional factors that may be contributing to the suboptimal response to rhGH remains uncertain.

Given the evidence suggesting that the ANKRD11 gene acts as a potential tumor suppressor due to its interaction with the p53 protein, particular attention should be paid to the safety profile of rhGH therapy, particularly oncogenic risks [ 126 ]. However, observational studies have reported no increased risk of mortality or the development of primary cancers among pediatric patients receiving rhGH treatment [ 127 , 128 , 129 ]. The implementation of cancer surveillance in patients clinically diagnosed as having KBGS due to ANKRD11 variants has been previously contemplated, and few patients were reported to develop malignant tumors [ 130 , 131 ]. Short stature is one of all KBGS phenotypes that can be effectively treated with growth-promoting drugs, but there are few patients receiving rhGH treatment. The approval and accessibility of rhGH therapy for KBGS may be limited in certain countries, which highlights the imperative for further investigation and research within this specialized domain. In alignment with the recommendations proposed by Reynaert et al. [ 58 ], we advocate for a more favorable stance towards the implementation of short-term rhGH therapy for ANKRD11 variant-induced KBGS patients with severe short stature.

Underlying mechanisms of ANKRD11 variants causing short stature

Human longitudinal bone growth is persistently driven by the process of endochondral ossification within the epiphyseal growth plate that is characterized by three histologically distinct zones (resting, proliferative, and hypertrophic zones) throughout the stages of postnatal development [ 132 ]. As the slowly-cycling reserve cells, resting chondrocytes are maintained in a wingless-related integration site (Wnt)-inhibitory environment, and it contains a certain proportion of parathyroid hormone-related protein (PTHrP)-expressing skeletal stem-like cells producing rapidly proliferating columnar chondrocytes parallel to the direction of bone elongation [ 133 ]. Proliferative zone chondrocytes will differentiate into hypertrophic chondrocytes characterized by specific expression of type X collagen gene ( Col10a1 ), and further undergo apoptosis or osteoblasts trans-differentiation, thereby contributing to bone elongation [ 134 , 135 ]. The orchestrated differentiation of chondrocytes within the growth plate is governed by a complex interplay of numerous genes that are involved in a variety of signaling pathways, including hormonal signaling, paracrine signaling, intracellular pathways and extracellular matrix homeostasis (Fig.  5 ) [ 68 , 136 , 137 , 138 ]. Functional variants in any of these genes can disrupt the growth plate chondrogenesis and impair the subsequent bone elongation. It was hypothesized that ANKRD11 plays a direct role in the transcriptional regulation of certain critical genes via intracellular pathways in the process of growth plate development [ 68 ]. In a prior investigation, Yoda mice with an N-ethyl-N-nitrosourea (ENU)-induced mutation in the ANKRD11 gene, exhibited a markedly reduced body size and presented with a phenotype reminiscent of osteoporosis compared to littermate controls [ 3 ]. However, no alterations were observed in the histological structure of the tibial growth plate and plasma IGF-1 level between six-month-old Yoda mice and wild-type mice. Given that growth plate in rodents do not undergo fusion but are instead subject to an age-related decrease following sexual maturation [ 139 ], it can be inferred that adult mice with ANKRD11 deficiency may not well accurately reflect the aberrant differentiation process of growth plate chondrocytes during rapid bone elongation. Data obtained from the International Mouse Phenotyping Consortium (IMPC) indicate that C57BL/6 N mice carrying a heterozygous ANKRD11 tm1b(EUCOMM)Wtsi allele exhibited a reduction in body length when compared to their littermate controls ( https://www.mousephenotype.org/data/genes/MGI:1924337 ). Additionally, mice with a conditional deletion of the ANKRD11 gene in neural crest cells dispalyed ossification centers that were either incapable of expansion or failed to fuse, demonstrating the critical regulatory role of ANKRD11 gene in intramembranous ossification [ 22 ]. In vitro studies further revealed that ANKRD11 was capable of enhancing the transactivation of the p21 gene, a key factor in the chondrogenic differentiation of ATDC5 cells induced by insulin supplements [ 61 ]. The chondrogenic differentiation of ATDC5 cells induced by insulin-transferrin-selenium is a widely recognized in vitro model mimicking endochondral ossification [ 140 , 141 , 142 , 143 ]. The potential role of the ANKRD11-p21 signaling pathway in growth plate development as a plausible mechanism to elucidate the short stature observed in KBGS patients warrants further investigation. To elucidate the functional mechanisms of the ANKRD11 gene in the physiological process of growth plate development, it is essential to conduct further study employing a mouse model with chondrocyte-specific ANKRD11 ablation, utilizing the CRISPR/Cas9 and Cre/LoxP recombination system.

Disease-causing genes associated with short stature through affecting the endochondral ossification of epiphyseal growth plate. The ANKRD11 gene may be implicated in this process as a transcription regulator. RZ: resting zone, PZ: proliferative zone, PHZ: prehypertrophic zone, HZ: hypertrophic zone

Conclusions

Frameshift and nonsense were the most common types of ANKRD11 variants. Approximately half of the KBGS patients harboring ANKRD11 variants had short stature. However, the current study has not established a clear correlation between the genotype and this phenotypic manifestation. Some patients harboring ANKRD11 variants may initially be diagnosed as syndromic short stature due to limited recognition of KBGS. While patients with ANKRD11 variants exhibit a positive response to rhGH therapy, further investigation is warranted to substantiate its efficacy and safety. Functional variants in the ANKRD11 gene can potentially disrupt the longitudinal growth of bones by influencing the orderly differentiation process of growth plate chondrocytes, which needs deeper investigation through fundamental research to elucidate its underlying mechanisms.

Data availability

The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding authors.

Abbreviations

American college of medical genetics and genomics

Activation domain

Alteration/deficiency in activation 3

Amplified in breast cancer 1

Association for molecular pathology

Ankyrin repeats-containing cofactor

Ankyrin repeat domain containing-protein 11

One-way analysis of variance

Brain-derived neurotrophic factor

[(CAMP-response-element binding protein)-binding protein]-associated factor

(CAMP-response-element binding protein)-binding protein

CAMP-response-element binding protein

Chronic renal insufficiency

Electroencephalogram

N-ethyl-N-nitrosourea

Estrogen receptor

Food and drug administration

Growth hormone

Growth hormone deficiency

Growth hormone insensitivity

Genome-wide association study

Histone acetylase

Histone deacetylase

Histone 3 lysine 9

Histone 4 lysine 5

Histone 4 lysine 8

Histone 4 lysine 16

Height standard deviation score

Hypertrophic zone

Insulin-like growth factor

Insulin-like growth factor binding protein 3

Isolated growth hormone deficiency

Indian hedgehog

International mouse phenotyping onsortium

Insertion or deletion

Intelligence quotient

Idiopathic short stature

Ligand-binding domain

Multiple pituitary hormone deficiency

Magnetic resonance imaging

Nuclear localization signal

Natriuretic peptide receptor 2

Nuclear receptors

Noonan syndrome

Online mendelian inheritance in man

Per-Arnt-Sim

Parathyroid hormone-related protein

Protein-truncating variant

Prader-Willi syndrome

Proliferative zone

Repression domain

Recombinant human growth hormone

Resting zone

Standard deviation

Standard deviation score

Small for gestational age

Single nucleotide polymorphism

Secondary ossification center

Transcriptional enhanced associate domain

Tyrosine receptor kinase B

Turner syndrome

Whole exome sequencing

Wingless-related integration site

Yes-associated protein

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This work was supported by Research Fund for Academician Lin He New Medicine (JYHL2019FZD01) and the PhD Research Foundation of Affiliated Hospital of Jining Medical University (2018-BS-007), and was partly supported by Shandong Traditional Chinese Medicine Science and Technology Development Plans Project (2019 − 0486).

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Dongye He, Mei Zhang, Yanying Li, Fupeng Liu & Bo Ban

Medical Research Center, Affiliated Hospital of Jining Medical University, Jining, China

Dongye He, Fupeng Liu & Bo Ban

Chinese Research Center for Behavior Medicine in Growth and Development, Jining, China

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DYH performed the literature search and wrote the manuscript. MZ, YYL and FPL performed the literature search and collected ANKRD11 variants from ClinVar database. BB provided guidance on the data collection and critically revised the manuscript. All authors have reviewed and approved the final manuscript.

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He, D., Zhang, M., Li, Y. et al. Insights into the ANKRD11 variants and short-stature phenotype through literature review and ClinVar database search. Orphanet J Rare Dis 19 , 292 (2024). https://doi.org/10.1186/s13023-024-03301-y

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Received : 03 April 2023

Accepted : 05 August 2024

Published : 12 August 2024

DOI : https://doi.org/10.1186/s13023-024-03301-y

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