thesis databases

Open Access Theses and Dissertations

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Recent Additions

See all of this week’s new additions.

About OATD.org

OATD.org aims to be the best possible resource for finding open access graduate theses and dissertations published around the world. Metadata (information about the theses) comes from over 1100 colleges, universities, and research institutions . OATD currently indexes 7,241,108 theses and dissertations.

About OATD (our FAQ) .

Visual OATD.org

We’re happy to present several data visualizations to give an overall sense of the OATD.org collection by county of publication, language, and field of study.

You may also want to consult these sites to search for other theses:

• Google Scholar
• NDLTD , the Networked Digital Library of Theses and Dissertations. NDLTD provides information and a search engine for electronic theses and dissertations (ETDs), whether they are open access or not.
• Proquest Theses and Dissertations (PQDT), a database of dissertations and theses, whether they were published electronically or in print, and mostly available for purchase. Access to PQDT may be limited; consult your local library for access information.

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EBSCO Open Dissertations

EBSCO Open Dissertations makes electronic theses and dissertations (ETDs) more accessible to researchers worldwide. The free portal is designed to benefit universities and their students and make ETDs more discoverable. 

Increasing Discovery & Usage of ETD Research

EBSCO Open Dissertations is a collaboration between EBSCO and BiblioLabs to increase traffic and discoverability of ETD research. You can join the movement and add your theses and dissertations to the database, making them freely available to researchers everywhere while increasing traffic to your institutional repository. 

EBSCO Open Dissertations extends the work started in 2014, when EBSCO and the H.W. Wilson Foundation created American Doctoral Dissertations which contained indexing from the H.W. Wilson print publication, Doctoral Dissertations Accepted by American Universities, 1933-1955. In 2015, the H.W. Wilson Foundation agreed to support the expansion of the scope of the American Doctoral Dissertations database to include records for dissertations and theses from 1955 to the present.

How Does EBSCO Open Dissertations Work?

Your ETD metadata is harvested via OAI and integrated into EBSCO’s platform, where pointers send traffic to your IR.

EBSCO integrates this data into their current subscriber environments and makes the data available on the open web via opendissertations.org .

You might also be interested in:

Global ETD Search

Search the 6,479,554 electronic theses and dissertations contained in the NDLTD archive:

The archive supports advanced filtering and boolean search.

EBSCO Open Dissertations

Search millions of electronic theses and dissertations (etds).

With EBSCO Open Dissertations, institutions and students are offered an innovative approach to driving additional traffic to ETDs in institutional repositories. Our goal is to help make their students’ theses and dissertations as widely visible and cited as possible.

This approach extends the work started in 2014, when EBSCO and the H.W. Wilson Foundation created American Doctoral Dissertations which contained indexing from the H.W. Wilson print publication, Doctoral Dissertations Accepted by American Universities, 1933-1955. In 2015, the H.W. Wilson Foundation agreed to support the expansion of the scope of the American Doctoral Dissertations database to include records for dissertations and theses from 1955 to the present.

Get involved in the EBSCO Open Dissertations project and make your electronic theses and dissertations freely available to researchers everywhere. Please contact Margaret Richter for more information.

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Open Access Theses and Dissertations (OATD)

OATD.org provides open access graduate theses and dissertations published around the world. Metadata (information about the theses) comes from over 1100 colleges, universities, and research institutions. OATD currently indexes 6,654,285 theses and dissertations.

Open Access Theses and Dissertations

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ProQuest Dissertations & Theses Global

• What is ProQuest Dissertations & Theses Global
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Webinar recordings, powerpoint presentations, additional resources, support center articles.

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ProQuest Dissertations & Theses Global   is a wealth of unique global scholarship, which is a credible and quality source to Uncover the Undiscovered research insights and intelligence in easiest and most effective ways. The equitable discoverability of more than 5.8 million dissertations and theses with coverage from year 1637, allows researchers to amplify diverse voices and place their research in a global context. The database offers nearly 3.2 million full texts for most of the dissertations added since 1997.

By leveraging the rich citation data found in ProQuest Dissertations & Theses Global and with new citation insight tool, researchers can benefit from focused pathways of discovery to build foundational knowledge on various research topics. Over 200,000 new dissertations and theses are added to the database each year to enrich the citation data continuously.

For more information about the ProQuest Dissertations & Theses Global , navigate to the Content Page .

ProQuest Dissertations & Theses Global   Database  is also part of ProQuest One Academic .  ProQuest Dissertations & Theses Global resides on the ProQuest Platform. For more information about the ProQuest Platform search and display features, see the  ProQuest Platform LibGuide .

The Dissertations Bootcamp eLearning Modules are a free resource that help support graduate student planning, writing, and research.

ProQuest Dissertations and Theses for the Student, Citation Connections

Here you can have a preview of the new features just launched for the Cited Reference documents in ProQuest Dissertations & Theses Global.

ProQuest Dissertations and Theses for the Librarian

Intended for Librarians who want to learn how to use the database's advanced search to support subject area research at their institution. Duration: 2 minutes.

ProQuest Dissertations and Theses for the Student, Searching Titles and Languages

This session reviews how Students, both Masters or PhD, can use the database's advanced search to identify known dissertations by title and search/analyze by languages other than English. Duration: 3 minutes.

ProQuest Dissertations and Theses for the Student, Searching Names

This session reviews how Students, both Masters or Ph, can use the database's advanced search to identify dissertations of known Authors or Advisors and further refine/analyze them. Duration: 4 minutes.

ProQuest Dissertations and Theses for the Student, Cited References

This session reviews how Students, both Masters or PhD, can use the dissertations to retrieve and explore further the Cited References. Duration: 4 minutes.

ProQuest Dissertations and Theses for the Student, Supplemental Files

This session reviews how Students, both Masters or PhD, can identify dissertations with Supplemental files which may contain useful materials for their graduate work. Duration: 3.5 minutes.

ProQuest Dissertations and Theses for the Student, Subject Searching

This session will show Students, both Masters or PhD, some Search techniques both Basic and Advanced to locate dissertations on a certain topic. Duration: 5.5 minutes.

Webinar Title : Best Practices for Searching ProQuest Dissertations and Theses Global

This session demonstrates how users can utilize the best practices of searching the " ProQuest Dissertations and Theses Global  database" to connect with relevant information for their academic work. Duration:  52 minutes.

Materials in English - Figures (Database size) and Platform features images now updated as of March 2023

• PQDT Global Basic Version PPT
• PQDT Global Advanced Version PPT
• PQDT Global Citation Connection PPT
• ProQuest ETD Dissemination Program
• ProQuest Dissertations & Theses Citation Index Training Assest: ProQuest Dissertations & Theses Citation Index PPT- May 2024
• Marketing Toolkit
• New! Embedded eLearning for Undergraduates
• Request Training
• Top Dissertations
• ProQuest Dissertations & Theses Citation Index
• FAQ- What’s New for PQDT
• ProQuest Dissertations & Theses Global Data Used in Research Projects
• New Change in ProQuest Dissertations & Theses Global (PQDT) Structure and its Impact on Usage Reports in 2023
• New Change in ProQuest Dissertations & Theses Global (PQDT) Structure and its Impact on Saved Searches & Alerts
• Best Practices for Incorporating ProQuest Dissertations & Theses Global Product into EBSCO Discovery
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• Last Updated: May 4, 2024 10:06 AM
• URL: https://proquest.libguides.com/pqdt

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ProQuest Dissertations & Theses Global

ProQuest Dissertations & Theses Global is the largest editorially curated repository of multi-disciplinary dissertations and theses in the world. It includes millions of full-text dissertations, the majority of which were published after 1997, but hundreds of thousands of titles published before 1997 are also available. In addition to the full-text content, citations for over 5 million dissertations and theses are included. Content comes from thousands of universities located in 100+ countries. The database increases in size by 200,000+ works each year, and is designated as the official dissertation repository by the United States Library of Congress.

E-learning modules, webinar recordings, and additional resources are available at the ProQuest Dissertations & Theses Global Libguide .

Coverage : 1637- Provider : ProQuest

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ProQuest™ Dissertations & Theses Citation Index

The ProQuest™ Dissertations & Theses Citation Index (PQDT) is the world's most comprehensive curated collection of multi-disciplinary dissertations and theses, offering over 5.5 million records representing dissertations and theses from thousands of universities around the world.

Extending from they early 1600s to present, PQDT coverage is broadly multidisciplinary and includes foundational research in the life sciences, mathematics, computer science, engineering, social sciences, and humanities. Within dissertations and theses is a wealth of scholarship, yet it is often overlooked because most go unpublished.

Key Features

The ProQuest Dissertations & Theses Citation Index will be a standalone database and included in an All Databases search by default. WoS users also have filter options available in each search so that they can search broadly and then narrow focus on a particular collection, subject category, document type, etc. If a user wants to locate dissertations or theses specifically, they can also search of ProQuest Dissertations & Theses Citation Index only.

Standalone and aggregated search

PQDT is included in ALL Database search and can also be searched as a unique collection.

Track citation activity in Web of Science Core Collection

Dissertations and theses that have been cited by Web of Science Core Collection records will include a citation count and a link to the citing articles.

Claim dissertation or theses to a Web of Science Researcher Profiles

Researchers can manually claim their dissertation or thesis to their Web of Science Researcher Profile and make it part of the public view of their profile.

Links to Full Text of dissertations and theses on ProQuest platform

Institutions that subscribe to PQDT Global on the ProQuest platform will be able to link directly to their entitled full text.

Note: ProQuest Dissertation and Theses Citation Index will be released to customers in two phases. Phase 1: In July 2023, ProQuest Dissertations and Theses Citation Index will go live with metadata records for 5.5+ million dissertations and theses. The records will not include cited reference indexing, which means that functionality such as Related Records and Cited References lists and associated navigation will not display. Phase 2: In late 2023, Linked Cited References lists and Related Records will be released to fully connect dissertations to the Web of Science citation network. If you have any questions regarding PQDT entitlement or functionality, please contact the Web of Science support team .

Reference management. Clean and simple.

The top list of academic research databases

2. Web of Science

5. ieee xplore, 6. sciencedirect, 7. directory of open access journals (doaj), get the most out of your academic research database, frequently asked questions about academic research databases, related articles.

Whether you are writing a thesis , dissertation, or research paper it is a key task to survey prior literature and research findings. More likely than not, you will be looking for trusted resources, most likely peer-reviewed research articles.

Academic research databases make it easy to locate the literature you are looking for. We have compiled the top list of trusted academic resources to help you get started with your research:

Scopus is one of the two big commercial, bibliographic databases that cover scholarly literature from almost any discipline. Besides searching for research articles, Scopus also provides academic journal rankings, author profiles, and an h-index calculator .

• Coverage: 90.6 million core records
• References: N/A
• Discipline: Multidisciplinary
• Access options: Limited free preview, full access by institutional subscription only
• Provider: Elsevier

Web of Science also known as Web of Knowledge is the second big bibliographic database. Usually, academic institutions provide either access to Web of Science or Scopus on their campus network for free.

• Coverage: approx. 100 million items
• References: 1.4 billion
• Access options: institutional subscription only
• Provider: Clarivate (formerly Thomson Reuters)

PubMed is the number one resource for anyone looking for literature in medicine or biological sciences. PubMed stores abstracts and bibliographic details of more than 30 million papers and provides full text links to the publisher sites or links to the free PDF on PubMed Central (PMC) .

• Coverage: approx. 35 million items
• Discipline: Medicine and Biological Sciences
• Access options: free
• Provider: NIH

For education sciences, ERIC is the number one destination. ERIC stands for Education Resources Information Center, and is a database that specifically hosts education-related literature.

• Coverage: approx. 1.6 million items
• Discipline: Education
• Provider: U.S. Department of Education

IEEE Xplore is the leading academic database in the field of engineering and computer science. It's not only journal articles, but also conference papers, standards and books that can be search for.

• Coverage: approx. 6 million items
• Discipline: Engineering
• Provider: IEEE (Institute of Electrical and Electronics Engineers)

ScienceDirect is the gateway to the millions of academic articles published by Elsevier, 1.4 million of which are open access. Journals and books can be searched via a single interface.

• Coverage: approx. 19.5 million items

The DOAJ is an open-access academic database that can be accessed and searched for free.

• Coverage: over 8 million records
• Provider: DOAJ

JSTOR is another great resource to find research papers. Any article published before 1924 in the United States is available for free and JSTOR also offers scholarships for independent researchers.

• Coverage: more than 12 million items
• Provider: ITHAKA

Start using a reference manager like Paperpile to save, organize, and cite your references. Paperpile integrates with PubMed and many popular databases, so you can save references and PDFs directly to your library using the Paperpile buttons:

Scopus is one of the two big commercial, bibliographic databases that cover scholarly literature from almost any discipline. Beside searching for research articles, Scopus also provides academic journal rankings, author profiles, and an h-index calculator .

PubMed is the number one resource for anyone looking for literature in medicine or biological sciences. PubMed stores abstracts and bibliographic details of more than 30 million papers and provides full text links to the publisher sites or links to the free PDF on PubMed Central (PMC)

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Theses & Dissertation Databases

Use these databases to find dissertations and theses.

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Open access theses and dissertations (oatd).

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• Databases by Type: WPI Student Research: IQPs & MQPs; Theses & Dissertations by No Preference Last Updated Jul 19, 2023 632 views this year

Dissertations & Theses Databases

ProQuest Dissertations & Theses (PQDT) Global is the world's most comprehensive collection of dissertations and theses from around the world, offering millions of works from thousands of universities. Each year hundreds of thousands of works are added. Full-text coverage spans from 1743 to the present, with citation coverage dating back to 1637.

Search Digital WPI for electronic files of completed WPI graduate theses & dissertations from 2004 to present (and selected earlier works).

Coverage: 2004 - Full Text: Yes

Coverage: 1980- Full Text: Yes

OpenDissertations.org is a collaboration between EBSCO and BiblioLabs that brings an innovative approach to increasing traffic and discoverability of ETD research. This new collaboration extends the work started in 2014, when EBSCO and the H.W. Wilson Foundation created American Doctoral Dissertations which contained indexing from the H.W. Wilson print publication, Doctoral Dissertations Accepted by American Universities, 1933-1955. In 2015, the H.W. Wilson Foundation agreed to support the expansion of the scope of the American Doctoral Dissertations database to include records for dissertations and theses from 1955 to the present.

Search keywords, authors, or titles to find complete citation information for many theses and dissertations completed in North America and Europe since 1861. Request items through WPI's ILLiad Interlibrary loan service.

Coverage: 1861- Full Text: No

Catalog of books (and other materials) in libraries worldwide.

Coverage: 1200- Full Text: No

Additional Websites

• British Library Thesis Service
• Caltech Theses
• Center for Research Libraries foreign dissertations
• Cybertesis.net Provides access to many theses from Universidad Nacional Mayor de San Marcos (National University of San Marcos) in Peru
• EThOS Full text of theses from the British Library and other universities in Great Britain. This is running in beta at the moment
• MIT Document Services: Master's and Doctoral Theses
• University of Queensland Library Catalogue For global works try national library catalog of specific countries
• Open Access Theses and Dissertations OATD.org aims to be the best possible resource for finding open access graduate theses and dissertations published around the world. Metadata (information about the theses) comes from over 1100 colleges, universities, and research institutions. OATD currently indexes 6,595,987 theses and dissertations.
• Theses Canada Portal
• Last Updated: Jul 19, 2023 9:35 AM
• URL: https://libguides.wpi.edu/dissertations

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Open Access Theses & Dissertations (OATD)

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An index of over 1.6 million electronic theses and dissertations (ETDs). To the extent possible, the index is limited to records of graduate-level theses that are freely available online.

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How to search for Harvard dissertations

• DASH , Digital Access to Scholarship at Harvard, is the university's central, open-access repository for the scholarly output of faculty and the broader research community at Harvard.  Most Ph.D. dissertations submitted from  March 2012 forward  are available online in DASH.
• Check HOLLIS, the Library Catalog, and refine your results by using the   Advanced Search   and limiting Resource  Type   to Dissertations
• Search the database  ProQuest Dissertations & Theses Global Don't hesitate to  Ask a Librarian  for assistance.

How to search for Non-Harvard dissertations

Library Database:

• ProQuest Dissertations & Theses Global

Free Resources:

• Many  universities  provide full-text access to their dissertations via a digital repository.  If you know the title of a particular dissertation or thesis, try doing a Google search.  

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• Published: 03 May 2024

A dataset for measuring the impact of research data and their curation

• Libby Hemphill   ORCID: orcid.org/0000-0002-3793-7281 1 , 2 ,
• Andrea Thomer 3 ,
• Sara Lafia 1 ,
• Lizhou Fan 2 ,
• David Bleckley   ORCID: orcid.org/0000-0001-7715-4348 1 &
• Elizabeth Moss 1  

Scientific Data volume  11 , Article number:  442 ( 2024 ) Cite this article

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• Research data
• Social sciences

Science funders, publishers, and data archives make decisions about how to responsibly allocate resources to maximize the reuse potential of research data. This paper introduces a dataset developed to measure the impact of archival and data curation decisions on data reuse. The dataset describes 10,605 social science research datasets, their curation histories, and reuse contexts in 94,755 publications that cover 59 years from 1963 to 2022. The dataset was constructed from study-level metadata, citing publications, and curation records available through the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan. The dataset includes information about study-level attributes (e.g., PIs, funders, subject terms); usage statistics (e.g., downloads, citations); archiving decisions (e.g., curation activities, data transformations); and bibliometric attributes (e.g., journals, authors) for citing publications. This dataset provides information on factors that contribute to long-term data reuse, which can inform the design of effective evidence-based recommendations to support high-impact research data curation decisions.

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Background & summary.

Recent policy changes in funding agencies and academic journals have increased data sharing among researchers and between researchers and the public. Data sharing advances science and provides the transparency necessary for evaluating, replicating, and verifying results. However, many data-sharing policies do not explain what constitutes an appropriate dataset for archiving or how to determine the value of datasets to secondary users 1 , 2 , 3 . Questions about how to allocate data-sharing resources efficiently and responsibly have gone unanswered 4 , 5 , 6 . For instance, data-sharing policies recognize that not all data should be curated and preserved, but they do not articulate metrics or guidelines for determining what data are most worthy of investment.

Despite the potential for innovation and advancement that data sharing holds, the best strategies to prioritize datasets for preparation and archiving are often unclear. Some datasets are likely to have more downstream potential than others, and data curation policies and workflows should prioritize high-value data instead of being one-size-fits-all. Though prior research in library and information science has shown that the “analytic potential” of a dataset is key to its reuse value 7 , work is needed to implement conceptual data reuse frameworks 8 , 9 , 10 , 11 , 12 , 13 , 14 . In addition, publishers and data archives need guidance to develop metrics and evaluation strategies to assess the impact of datasets.

Several existing resources have been compiled to study the relationship between the reuse of scholarly products, such as datasets (Table  1 ); however, none of these resources include explicit information on how curation processes are applied to data to increase their value, maximize their accessibility, and ensure their long-term preservation. The CCex (Curation Costs Exchange) provides models of curation services along with cost-related datasets shared by contributors but does not make explicit connections between them or include reuse information 15 . Analyses on platforms such as DataCite 16 have focused on metadata completeness and record usage, but have not included related curation-level information. Analyses of GenBank 17 and FigShare 18 , 19 citation networks do not include curation information. Related studies of Github repository reuse 20 and Softcite software citation 21 reveal significant factors that impact the reuse of secondary research products but do not focus on research data. RD-Switchboard 22 and DSKG 23 are scholarly knowledge graphs linking research data to articles, patents, and grants, but largely omit social science research data and do not include curation-level factors. To our knowledge, other studies of curation work in organizations similar to ICPSR – such as GESIS 24 , Dataverse 25 , and DANS 26 – have not made their underlying data available for analysis.

This paper describes a dataset 27 compiled for the MICA project (Measuring the Impact of Curation Actions) led by investigators at ICPSR, a large social science data archive at the University of Michigan. The dataset was originally developed to study the impacts of data curation and archiving on data reuse. The MICA dataset has supported several previous publications investigating the intensity of data curation actions 28 , the relationship between data curation actions and data reuse 29 , and the structures of research communities in a data citation network 30 . Collectively, these studies help explain the return on various types of curatorial investments. The dataset that we introduce in this paper, which we refer to as the MICA dataset, has the potential to address research questions in the areas of science (e.g., knowledge production), library and information science (e.g., scholarly communication), and data archiving (e.g., reproducible workflows).

We constructed the MICA dataset 27 using records available at ICPSR, a large social science data archive at the University of Michigan. Data set creation involved: collecting and enriching metadata for articles indexed in the ICPSR Bibliography of Data-related Literature against the Dimensions AI bibliometric database; gathering usage statistics for studies from ICPSR’s administrative database; processing data curation work logs from ICPSR’s project tracking platform, Jira; and linking data in social science studies and series to citing analysis papers (Fig.  1 ).

Steps to prepare MICA dataset for analysis - external sources are red, primary internal sources are blue, and internal linked sources are green.

Enrich paper metadata

The ICPSR Bibliography of Data-related Literature is a growing database of literature in which data from ICPSR studies have been used. Its creation was funded by the National Science Foundation (Award 9977984), and for the past 20 years it has been supported by ICPSR membership and multiple US federally-funded and foundation-funded topical archives at ICPSR. The Bibliography was originally launched in the year 2000 to aid in data discovery by providing a searchable database linking publications to the study data used in them. The Bibliography collects the universe of output based on the data shared in each study through, which is made available through each ICPSR study’s webpage. The Bibliography contains both peer-reviewed and grey literature, which provides evidence for measuring the impact of research data. For an item to be included in the ICPSR Bibliography, it must contain an analysis of data archived by ICPSR or contain a discussion or critique of the data collection process, study design, or methodology 31 . The Bibliography is manually curated by a team of librarians and information specialists at ICPSR who enter and validate entries. Some publications are supplied to the Bibliography by data depositors, and some citations are submitted to the Bibliography by authors who abide by ICPSR’s terms of use requiring them to submit citations to works in which they analyzed data retrieved from ICPSR. Most of the Bibliography is populated by Bibliography team members, who create custom queries for ICPSR studies performed across numerous sources, including Google Scholar, ProQuest, SSRN, and others. Each record in the Bibliography is one publication that has used one or more ICPSR studies. The version we used was captured on 2021-11-16 and included 94,755 publications.

To expand the coverage of the ICPSR Bibliography, we searched exhaustively for all ICPSR study names, unique numbers assigned to ICPSR studies, and DOIs 32 using a full-text index available through the Dimensions AI database 33 . We accessed Dimensions through a license agreement with the University of Michigan. ICPSR Bibliography librarians and information specialists manually reviewed and validated new entries that matched one or more search criteria. We then used Dimensions to gather enriched metadata and full-text links for items in the Bibliography with DOIs. We matched 43% of the items in the Bibliography to enriched Dimensions metadata including abstracts, field of research codes, concepts, and authors’ institutional information; we also obtained links to full text for 16% of Bibliography items. Based on licensing agreements, we included Dimensions identifiers and links to full text so that users with valid publisher and database access can construct an enriched publication dataset.

Gather study usage data

ICPSR maintains a relational administrative database, DBInfo, that organizes study-level metadata and information on data reuse across separate tables. Studies at ICPSR consist of one or more files collected at a single time or for a single purpose; studies in which the same variables are observed over time are grouped into series. Each study at ICPSR is assigned a DOI, and its metadata are stored in DBInfo. Study metadata follows the Data Documentation Initiative (DDI) Codebook 2.5 standard. DDI elements included in our dataset are title, ICPSR study identification number, DOI, authoring entities, description (abstract), funding agencies, subject terms assigned to the study during curation, and geographic coverage. We also created variables based on DDI elements: total variable count, the presence of survey question text in the metadata, the number of author entities, and whether an author entity was an institution. We gathered metadata for ICPSR’s 10,605 unrestricted public-use studies available as of 2021-11-16 ( https://www.icpsr.umich.edu/web/pages/membership/or/metadata/oai.html ).

To link study usage data with study-level metadata records, we joined study metadata from DBinfo on study usage information, which included total study downloads (data and documentation), individual data file downloads, and cumulative citations from the ICPSR Bibliography. We also gathered descriptive metadata for each study and its variables, which allowed us to summarize and append recoded fields onto the study-level metadata such as curation level, number and type of principle investigators, total variable count, and binary variables indicating whether the study data were made available for online analysis, whether survey question text was made searchable online, and whether the study variables were indexed for search. These characteristics describe aspects of the discoverability of the data to compare with other characteristics of the study. We used the study and series numbers included in the ICPSR Bibliography as unique identifiers to link papers to metadata and analyze the community structure of dataset co-citations in the ICPSR Bibliography 32 .

Process curation work logs

Researchers deposit data at ICPSR for curation and long-term preservation. Between 2016 and 2020, more than 3,000 research studies were deposited with ICPSR. Since 2017, ICPSR has organized curation work into a central unit that provides varied levels of curation that vary in the intensity and complexity of data enhancement that they provide. While the levels of curation are standardized as to effort (level one = less effort, level three = most effort), the specific curatorial actions undertaken for each dataset vary. The specific curation actions are captured in Jira, a work tracking program, which data curators at ICPSR use to collaborate and communicate their progress through tickets. We obtained access to a corpus of 669 completed Jira tickets corresponding to the curation of 566 unique studies between February 2017 and December 2019 28 .

To process the tickets, we focused only on their work log portions, which contained free text descriptions of work that data curators had performed on a deposited study, along with the curators’ identifiers, and timestamps. To protect the confidentiality of the data curators and the processing steps they performed, we collaborated with ICPSR’s curation unit to propose a classification scheme, which we used to train a Naive Bayes classifier and label curation actions in each work log sentence. The eight curation action labels we proposed 28 were: (1) initial review and planning, (2) data transformation, (3) metadata, (4) documentation, (5) quality checks, (6) communication, (7) other, and (8) non-curation work. We note that these categories of curation work are very specific to the curatorial processes and types of data stored at ICPSR, and may not match the curation activities at other repositories. After applying the classifier to the work log sentences, we obtained summary-level curation actions for a subset of all ICPSR studies (5%), along with the total number of hours spent on data curation for each study, and the proportion of time associated with each action during curation.

Data Records

The MICA dataset 27 connects records for each of ICPSR’s archived research studies to the research publications that use them and related curation activities available for a subset of studies (Fig.  2 ). Each of the three tables published in the dataset is available as a study archived at ICPSR. The data tables are distributed as statistical files available for use in SAS, SPSS, Stata, and R as well as delimited and ASCII text files. The dataset is organized around studies and papers as primary entities. The studies table lists ICPSR studies, their metadata attributes, and usage information; the papers table was constructed using the ICPSR Bibliography and Dimensions database; and the curation logs table summarizes the data curation steps performed on a subset of ICPSR studies.

Studies (“ICPSR_STUDIES”): 10,605 social science research datasets available through ICPSR up to 2021-11-16 with variables for ICPSR study number, digital object identifier, study name, series number, series title, authoring entities, full-text description, release date, funding agency, geographic coverage, subject terms, topical archive, curation level, single principal investigator (PI), institutional PI, the total number of PIs, total variables in data files, question text availability, study variable indexing, level of restriction, total unique users downloading study data files and codebooks, total unique users downloading data only, and total unique papers citing data through November 2021. Studies map to the papers and curation logs table through ICPSR study numbers as “STUDY”. However, not every study in this table will have records in the papers and curation logs tables.

Papers (“ICPSR_PAPERS”): 94,755 publications collected from 2000-08-11 to 2021-11-16 in the ICPSR Bibliography and enriched with metadata from the Dimensions database with variables for paper number, identifier, title, authors, publication venue, item type, publication date, input date, ICPSR series numbers used in the paper, ICPSR study numbers used in the paper, the Dimension identifier, and the Dimensions link to the publication’s full text. Papers map to the studies table through ICPSR study numbers in the “STUDY_NUMS” field. Each record represents a single publication, and because a researcher can use multiple datasets when creating a publication, each record may list multiple studies or series.

Curation logs (“ICPSR_CURATION_LOGS”): 649 curation logs for 563 ICPSR studies (although most studies in the subset had one curation log, some studies were associated with multiple logs, with a maximum of 10) curated between February 2017 and December 2019 with variables for study number, action labels assigned to work description sentences using a classifier trained on ICPSR curation logs, hours of work associated with a single log entry, and total hours of work logged for the curation ticket. Curation logs map to the study and paper tables through ICPSR study numbers as “STUDY”. Each record represents a single logged action, and future users may wish to aggregate actions to the study level before joining tables.

Entity-relation diagram.

Technical Validation

We report on the reliability of the dataset’s metadata in the following subsections. To support future reuse of the dataset, curation services provided through ICPSR improved data quality by checking for missing values, adding variable labels, and creating a codebook.

All 10,605 studies available through ICPSR have a DOI and a full-text description summarizing what the study is about, the purpose of the study, the main topics covered, and the questions the PIs attempted to answer when they conducted the study. Personal names (i.e., principal investigators) and organizational names (i.e., funding agencies) are standardized against an authority list maintained by ICPSR; geographic names and subject terms are also standardized and hierarchically indexed in the ICPSR Thesaurus 34 . Many of ICPSR’s studies (63%) are in a series and are distributed through the ICPSR General Archive (56%), a non-topical archive that accepts any social or behavioral science data. While study data have been available through ICPSR since 1962, the earliest digital release date recorded for a study was 1984-03-18, when ICPSR’s database was first employed, and the most recent date is 2021-10-28 when the dataset was collected.

Curation level information was recorded starting in 2017 and is available for 1,125 studies (11%); approximately 80% of studies with assigned curation levels received curation services, equally distributed between Levels 1 (least intensive), 2 (moderately intensive), and 3 (most intensive) (Fig.  3 ). Detailed descriptions of ICPSR’s curation levels are available online 35 . Additional metadata are available for a subset of 421 studies (4%), including information about whether the study has a single PI, an institutional PI, the total number of PIs involved, total variables recorded is available for online analysis, has searchable question text, has variables that are indexed for search, contains one or more restricted files, and whether the study is completely restricted. We provided additional metadata for this subset of ICPSR studies because they were released within the past five years and detailed curation and usage information were available for them. Usage statistics including total downloads and data file downloads are available for this subset of studies as well; citation statistics are available for 8,030 studies (76%). Most ICPSR studies have fewer than 500 users, as indicated by total downloads, or citations (Fig.  4 ).

ICPSR study curation levels.

ICPSR study usage.

A subset of 43,102 publications (45%) available in the ICPSR Bibliography had a DOI. Author metadata were entered as free text, meaning that variations may exist and require additional normalization and pre-processing prior to analysis. While author information is standardized for each publication, individual names may appear in different sort orders (e.g., “Earls, Felton J.” and “Stephen W. Raudenbush”). Most of the items in the ICPSR Bibliography as of 2021-11-16 were journal articles (59%), reports (14%), conference presentations (9%), or theses (8%) (Fig.  5 ). The number of publications collected in the Bibliography has increased each decade since the inception of ICPSR in 1962 (Fig.  6 ). Most ICPSR studies (76%) have one or more citations in a publication.

ICPSR Bibliography citation types.

ICPSR citations by decade.

Usage Notes

The dataset consists of three tables that can be joined using the “STUDY” key as shown in Fig.  2 . The “ICPSR_PAPERS” table contains one row per paper with one or more cited studies in the “STUDY_NUMS” column. We manipulated and analyzed the tables as CSV files with the Pandas library 36 in Python and the Tidyverse packages 37 in R.

The present MICA dataset can be used independently to study the relationship between curation decisions and data reuse. Evidence of reuse for specific studies is available in several forms: usage information, including downloads and citation counts; and citation contexts within papers that cite data. Analysis may also be performed on the citation network formed between datasets and papers that use them. Finally, curation actions can be associated with properties of studies and usage histories.

This dataset has several limitations of which users should be aware. First, Jira tickets can only be used to represent the intensiveness of curation for activities undertaken since 2017, when ICPSR started using both Curation Levels and Jira. Studies published before 2017 were all curated, but documentation of the extent of that curation was not standardized and therefore could not be included in these analyses. Second, the measure of publications relies upon the authors’ clarity of data citation and the ICPSR Bibliography staff’s ability to discover citations with varying formality and clarity. Thus, there is always a chance that some secondary-data-citing publications have been left out of the bibliography. Finally, there may be some cases in which a paper in the ICSPSR bibliography did not actually obtain data from ICPSR. For example, PIs have often written about or even distributed their data prior to their archival in ICSPR. Therefore, those publications would not have cited ICPSR but they are still collected in the Bibliography as being directly related to the data that were eventually deposited at ICPSR.

In summary, the MICA dataset contains relationships between two main types of entities – papers and studies – which can be mined. The tables in the MICA dataset have supported network analysis (community structure and clique detection) 30 ; natural language processing (NER for dataset reference detection) 32 ; visualizing citation networks (to search for datasets) 38 ; and regression analysis (on curation decisions and data downloads) 29 . The data are currently being used to develop research metrics and recommendation systems for research data. Given that DOIs are provided for ICPSR studies and articles in the ICPSR Bibliography, the MICA dataset can also be used with other bibliometric databases, including DataCite, Crossref, OpenAlex, and related indexes. Subscription-based services, such as Dimensions AI, are also compatible with the MICA dataset. In some cases, these services provide abstracts or full text for papers from which data citation contexts can be extracted for semantic content analysis.

Code availability

The code 27 used to produce the MICA project dataset is available on GitHub at https://github.com/ICPSR/mica-data-descriptor and through Zenodo with the identifier https://doi.org/10.5281/zenodo.8432666 . Data manipulation and pre-processing were performed in Python. Data curation for distribution was performed in SPSS.

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Acknowledgements

We thank the ICPSR Bibliography staff, the ICPSR Data Curation Unit, and the ICPSR Data Stewardship Committee for their support of this research. This material is based upon work supported by the National Science Foundation under grant 1930645. This project was made possible in part by the Institute of Museum and Library Services LG-37-19-0134-19.

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Libby Hemphill, Sara Lafia, David Bleckley & Elizabeth Moss

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L.H. and A.T. conceptualized the study design, D.B., E.M., and S.L. prepared the data, S.L., L.F., and L.H. analyzed the data, and D.B. validated the data. All authors reviewed and edited the manuscript.

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Correspondence to Libby Hemphill .

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Hemphill, L., Thomer, A., Lafia, S. et al. A dataset for measuring the impact of research data and their curation. Sci Data 11 , 442 (2024). https://doi.org/10.1038/s41597-024-03303-2

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Received : 16 November 2023

Accepted : 24 April 2024

Published : 03 May 2024

DOI : https://doi.org/10.1038/s41597-024-03303-2

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