June was an incredibly busy month for the Data Curation Network – in addition to all of the activities listed in our monthly newsletter, DCN representatives were present at numerous in-person and virtual conferences.
DCN Curators– if you’re interested in participating in future research projects like these, consider signing up for a Special Interest Group or Committee. And if you’re not sure where to start, check out participation suggestions or reach out to your new Curator at Large, Dorris Scott!
June 6-9, 2022: Open Repositories
Poster by Sarah Wright, Wanda Marsolek, Hoa Luong, Susan Braxton, Sophia Lafferty-Hess, and Jake Carlson: “Researcher Approved: a Multi-institutional Survey of Depositors to Six Academic Data Repositories,” available at https://hdl.handle.net/11299/227932
Congrats to the authors of this poster for winning second place in the poster contest!
Abstract: In order to evaluate end user satisfaction with data curation services, we surveyed recent depositors over the past year and a half, regardless of whether they received curation locally or from DCN curators. The result was overwhelmingly positive: we enjoyed a high response rate and consistently laudatory feedback including many free-text responses testifying to the value of curation. In times of tight budgets and constricting services, it is good to have researcher testimonials and survey data to indicate the added value of curatorial review to the data sharing process, and evidence that a collaborative network of data curators benefits us all.
Presentation by Sarah Wright, Ted Habermann, Shawna Taylor, and Mikala Narlock: “Think Globally, Act Locally: The Importance of Elevating Data Repository Metadata to the Global Infrastructure,” available at: https://hdl.handle.net/11299/228001
Abstract: The Realities of Academic Data Sharing (RADS) Initiative has found that institutions and researchers create and have access to the most complete metadata, but that valuable metadata found in these local institutional repositories (IRs) are not making their way into global data infrastructure such as DataCite or Crossref. This panel examines the local to global spectrum of metadata completeness, including the challenges of obtaining quality metadata at a local level, specifically at Cornell University, and the loss of metadata during the transfer processes from IRs into global data infrastructure. By feeding local IR metadata into the global data infrastructure, the global infrastructure starts giving back in the form of these connections.
June 7-10, 2022: International Association for Social Science Information Service and Technology
Abstract: Growing beyond its original scope of shared staffing for data curation, the DCN has become a thriving community and sustainable organization that advocates for data curation and data curators and provides a unique platform for exploration and research. This presentation highlights efforts underway in the DCN and provides project updates including DCN’s new membership model and plans for ongoing sustainability, special interest groups, and research.
June 13-16, 2022: International Digital Curation Conference
Lightning talk presentation by Shawna Taylor and Ted Habermann: “Toward Reusability: Preliminary Metadata Best Practices From the Realities of Academic Data Sharing Initiative,” available at: https://doi.org/10.5281/zenodo.6642272
Abstract: The Realities of Academic Data Sharing (RADS) Initiative, funded by the National Science Foundation, is investigating institutional processes for improving research data FAIRness. Focal points of the RADS inquiry are to understand where researchers are sharing their data and to assess metadata quality, i.e., completeness, at six Data Curation Network (DCN) academic institutions: Cornell University, Duke University, University of Michigan, University of Minnesota, Washington University in St. Louis, and Virginia Tech. RADS is examining where researchers are storing their data, considering local institutional repositories and other popular repositories, and analyzing the completeness of the research data metadata stored in these institutional and other repositories. Metadata FAIRness (Findable, Accessible, Interoperable, Reusable) is used as the metric to assess metadata quality as FAIR complete.
Abstract: Through the Data Curation Network (DCN), members enable findable, accessible, interoperable, and reusable (FAIR) data through a shared curation model, education and outreach efforts, and research and advocacy. This work exists within a member- funded and member-driven organization, with a focus on sustainability and long-term growth. Members of the DCN help shape the future of data curation and enable FAIR data by sharing best practices, collaboratively addressing shared challenges, empowering and educating one another, and advocating for data curation broadly.
Stay up to date on all of the DCN publications and presentations– subscribe to our newsletter and watch for DCN representatives at future conferences!