In February 2024, the Data Curation Network provided feedback on the USDA’s Implementation Plan to Increase Public Access to USDA-Funded Research Results, Notice 2024-01673. We are excited to see and support the USDA’s continued efforts to provide access to invaluable data and research outputs, and submitted the following feedback (slightly edited from the full version), which we believe will strengthen the proposed plan.
We appreciate the USDA’s focus on long-term data preservation by including expenses related to publications and the management and curation of research data as allowable costs. Professional data curation and preservation are not inexpensive. We recommend that the USDA emphasize that publication of data, supplementary files, and/or code on publishers’ sites or GitHub is not equivalent to repository publication and curation and will not fulfill the USDA’s requirements. We also recommend that the USDA remind researchers that there may be existing institutional assistance and solutions for their open-access publishing and data sharing and preservation needs, such as institutional repositories and data curation services.
Regarding data associated with a publication, the requirement for data to be made “freely available and publicly accessible by default at the time of publication” (p.3) is clear but may be difficult for researchers dealing with large datasets associated with multiple publications. In an ideal world, researchers would actively curate data during the research so that datasets are ready to publish and share; the reality, in our experiences, is the opposite. Preparing data for publication is often an extensive process and may require additional processing time in order to align with FAIR principles. We recommend the USDA evaluate several anticipated scenarios of data release and sharing in its documentation, with clear guidance regarding the timeline for each.
Lastly, we propose that the USDA work with other federal agencies to further develop the required characteristics of a ‘good’ repository and to develop funding mechanisms to support improved accessibility to research datasets. We suggest that USDA researchers and data curators utilize relevant DCN primers to create more FAIR datasets. We also learned of efforts by the National Transportation Library to test and integrate the DCN CURATE(D) workflow for its curation practices. It may be useful for the National Agricultural Library to review the workflow for possible adoption of curation practices.
We are always happy to offer additional information through an email or meeting should it be useful. You can connect with the DCN via our Contact Form.
Mikala Narlock,
Director, Data Curation Network
With special thanks to Leslie Delserone, Laura Hjerpe, Sherry Lake, Matthew Murray, and Jon Petters for their comments and suggestions that are the foundation of this blog post and feedback.
The full response has been archived and is accessible at: https://hdl.handle.net/11299/261450