Seek and you may (not) find: A multi-institutional analysis of where research data are shared

Authors

Lisa R. Johnston, Data, Academic Planning & Institutional Research, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Alicia Hofelich Mohr, Liberal Arts Technologies and Innovation Services, University of Minnesota, Minneapolis, Minnesota, United States of America.
Joel Herndon, Center for Data and Visualization Sciences, Duke University Libraries, Duke University, Durham, North Carolina, United States of America.
Shawna Taylor, Association of Research Libraries, Washington, D.C., United States of America.
Jake R. Carlson, University at Buffalo Libraries, University at Buffalo, Buffalo, New York, United States of America.
Lizhao Ge, Milken Institute School of Public Health, George Washington University, Washington, D.C., United States of America.
Jennifer Moore, University Libraries, Washington University in St. Louis, St. Louis, Missouri, United States of America.
Jonathan Petters, Data Services, University Libraries, Virginia Tech, Blacksburg, Virginia, United States of America.
Wendy Kozlowski, Research Data and Open Scholarship, Cornell University Library, Cornell University, Ithaca, New York, United States of America.
Cynthia Hudson Vitale, Association of Research Libraries, Washington, DC., United States of America.

Document Type

Journal Article

Publication Date

1-1-2024

Journal

PloS one

Volume

19

Issue

4

DOI

10.1371/journal.pone.0302426

Abstract

Research data sharing has become an expected component of scientific research and scholarly publishing practice over the last few decades, due in part to requirements for federally funded research. As part of a larger effort to better understand the workflows and costs of public access to research data, this project conducted a high-level analysis of where academic research data is most frequently shared. To do this, we leveraged the DataCite and Crossref application programming interfaces (APIs) in search of Publisher field elements demonstrating which data repositories were utilized by researchers from six academic research institutions between 2012-2022. In addition, we also ran a preliminary analysis of the quality of the metadata associated with these published datasets, comparing the extent to which information was missing from metadata fields deemed important for public access to research data. Results show that the top 10 publishers accounted for 89.0% to 99.8% of the datasets connected with the institutions in our study. Known data repositories, including institutional data repositories hosted by those institutions, were initially lacking from our sample due to varying metadata standards and practices. We conclude that the metadata quality landscape for published research datasets is uneven; key information, such as author affiliation, is often incomplete or missing from source data repositories and aggregators. To enhance the findability, interoperability, accessibility, and reusability (FAIRness) of research data, we provide a set of concrete recommendations that repositories and data authors can take to improve scholarly metadata associated with shared datasets.

APA Citation

Johnston, Lisa R.; Hofelich Mohr, Alicia; Herndon, Joel; Taylor, Shawna; Carlson, Jake R.; Ge, Lizhao; Moore, Jennifer; Petters, Jonathan; Kozlowski, Wendy; and Hudson Vitale, Cynthia, "Seek and you may (not) find: A multi-institutional analysis of where research data are shared" (2024). GW Authored Works. Paper 4674.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/4674

Department

Public Health Student Works