Introducing 10 Things for Curating Reproducible and FAIR Research Webinar

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Introducing 10 Things for Curating Reproducible and FAIR Research 

Curation for FAIR and reproducible research is the process of reviewing and enhancing a research compendium for long-term reuse.  Given the replication crisis and requirements of most journals that data and code be submitted upon acceptance or made available upon request as a condition for publication, it is imperative that researchers provide high-quality reproduction materials (i.e., data, code, documentation) that underlie their research.

This webinar presents "10 Things for Curating Reproducible and FAIR Research”, which are guidelines designed for curators and researchers interested in publishing and archiving reproducible research output.  It will focus on the following: 

• Key issues in curating reproducible and FAIR (CURE-FAIR) research
• Practical strategies that ensure publication-ready and independently understandable packages of reproducible  research materials
• Best practices in archiving and publishing computationally reproducible studies that rely on quantitative data, primarily in the social sciences

These guidelines are intended primarily for data curators and information professionals who are charged with the publication and archival of FAIR and computationally reproducible research. Often the first reusers of the research compendium, curators have the opportunity to verify that a computation can be executed and that it can reproduce prespecified results. Curators can flag issues with a research compendium that precludes computational reproducibility and take actions to remedy problems or recommend an appropriate course of action prior to publication. 

Who Should Attend

While curation is often carried out near the end of the research lifecycle by data and archive professionals, there are many actions that other key stakeholders can take earlier in the lifecycle that can facilitate the production of FAIR and computationally reproducible research compendia. This webinar will be of interest also to researchers, publishers, editors, reviewers, and others who have a stake in creating, using, sharing, publishing, or preserving reproducible research.

This resource is primarily geared towards the social sciences. It is our hope, however, that it will serve as a starting point for the development of curatorial guidelines to extend beyond the specific concerns of the social sciences community. We believe it can extend to other domains and disciplines that use similar methods, especially those with similar curatorial concerns and requirements of archives or publishers.

Presenters

Limor Peer Associate Director for Research and Strategic Initiatives Department/Division Institution for Social and Policy Studies Yale University United States ORCID ID: 0000-0002-3234-1593   Limor oversees social science research infrastructure and process and led the creation of a specialized research data repository and the development of curation software that supports reproducible research at Yale.   Mandy Gooch Research Data Archivist The Odum Institute for Research in Social Science University of North Carolina at Chapel Hill United States ORCID ID: 0000-0002-1024-1989

Mandy works closely with students, faculty, and staff providing data management consultation and training. Additionally, she oversees the data verification service offered by Odum Institute and works with editors of social science journals to implement and maintain their data verification workflows throughout the manuscript submission process.

Tom Honeyman Software Program Manager Australian Research Data Commons (ARDC) Australia ORCID ID: 0000-0001-9448-4023 Tom is working towards the recognition of software as a first-class research output.

Thu-Mai Christian Assistant Director for Archives The Odum Institute for Research in Social Science University of North Carolina at Chapel Hill United States ORCID ID: 0000-0002-3658-9692 Thu-Mai is responsible for the day-to-day operations of the Odum Institute Data Archive as well as establishing and enforcing policies in accordance with archival standards and best practices.

Florio Arguillas Research Associate Cornell Center for Social Sciences (CCSS) Cornell University United States ORCID ID: 0000-0002-2000-3722 Florio oversees the data and reproducibility services at the Cornell Center for Social Sciences.  Additionally, he assists and trains researchers on qualitative and qualitative data management, processing, and analysis; strategies for data anonymization, and making transparent and reproducible research.

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