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Archival expectations and requirements for researchers’ data and code are changing rapidly, both among publishers and institutions, in response to what has been referred to as a “reproducibility crisis.” In an effort to address this crisis, a number of publishers have added requirements or recommendations to increase the availability of supporting information behind the research, and academic institutions have followed. Librarians should focus on ways to make it easier for researchers to effectively share their data and code with reproducibility in mind. At the Cornell Center for Social Sciences, we have instituted a Results Reproduction Service (R-Squared) for Cornell researchers. Part of this service includes archiving the R-Squared package in our CoreTrustSeal certified Data and Reproduction Archive, which has been rebuilt to accommodate both the unique requirements of those packages and the traditional role of our data archive. Librarians need to consider roles that archives and institutional repositories can play in supporting researchers with reproducibility initiatives. Our commentary closes with some suggestions for more information and training.


data archiving, data librarianship, research data, research reproduction


The authors would like to acknowledge the contributions of CCSS staff, especially Florio Arguillas, to our understanding of quantitative reproduction methods and Brandon Kowalski to the design of CCSS’s Data & Reproduction Archive. We would also like to thank Kathleen Weldon of The Roper Center for Public Opinion Research for reviewing the draft of this manuscript. Lastly, we would like to thank William Block, former director of the Cornell Institute for Social and Economic Research. Disclosures: The content of this article is based upon a lightning talk presentation at RDAP Summit 2021 titled “Preparing a Data Archive or Repository for Changing Research Data and Materials Retention Policies” available at https://osf.io/ug5ty.

Corresponding Author

Jonathan Bohan, Cornell Center for Social Sciences, 391 Pine Tree Road, Ithaca, NY 14850 USA; jb2287@cornell.edu

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Copyright © 2021 Bohan & Kellam. This is an open access article licensed under the terms of the Creative Commons Attribution License.

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