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Article Type

Full-Length Paper

Publication Date

2021-03-01

DOI

10.7191/jeslib.2021.1191

Abstract

Objective: Investigate how different groups of depositors vary in their use of optional data curation features that provide support for FAIR research data in the Harvard Dataverse repository.

Methods: A numerical score based upon the presence or absence of characteristics associated with the use of optional features was assigned to each of the 29,295 datasets deposited in Harvard Dataverse between 2007 and 2019. Statistical analyses were performed to investigate patterns of optional feature use amongst different groups of depositors and their relationship to other dataset characteristics.

Results: Members of groups make greater use of Harvard Dataverse's optional features than individual researchers. Datasets that undergo a data curation review before submission to Harvard Dataverse, are associated with a publication, or contain restricted files also make greater use of optional features.

Conclusions: Individual researchers might benefit from increased outreach and improved documentation about the benefits and use of optional features to improve their datasets' level of curation beyond the FAIR-informed support that the Harvard Dataverse repository provides by default. Platform designers, developers, and managers may also use the numerical scoring approach to explore how different user groups use optional application features.

Keywords

research data, optional feature use, application users, research data curation, research data repositories, Harvard Dataverse, Dataverse Project

Data Availability

Data associated with this study is publicly available in the Harvard Dataverse repository (https://doi.org/10.7910/DVN/9STGWE).

Acknowledgments

I thank Mercè Crosas and members of the Harvard Dataverse data curation team, Sonia Barbosa and Julian Gautier for making the repository and its research datasets available for this quantitative investigation.

Corresponding Author

Ceilyn Boyd, Simmons University, School of Library and Information Science, Boston, MA 02115; ceilyn.boyd@simmons.edu

Rights and Permissions

© 2021 Boyd. This is an open access article licensed under the terms of the Creative Commons Attribution License.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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