[Thu-Mai Lewis]

The goal of the CURE-FAIR working group is to establish guidelines and standards for curating for reproducible and FAIR data and code.

Become a Member

RDA Group Page: https://www.rd-alliance.org/groups/cure-fair-wg
Case Statement: https://www.rd-alliance.org/node/66744/case-statement
OSF Project Page: https://osf.io/mhj97/
Subgroup Sign-up: https://bit.ly/35lHj34

Subgroup 1: CURE-FAIR Definitions

Aim
Provide a broader understanding of what it means to curate research artifacts (e.g., data, code, software) for the purposes of supporting research reproducibility in the context of FAIR principles

Charge
▪ Identify existing definitions of curation for reproducibility
▪ Align definitions of curation for reproducibility to FAIR principles
▪ Address incongruencies between CURE definitions and FAIR principles

Output
Report that summarizes existing definitions of curation for reproducibility and the degree to which these definitions align with FAIR principles

Subgroup 2: CURE-FAIR Practices

Aim
Explore curation for reproducibility practices as tey are implemented in various disciplinary domains and by different stakeholder groups

Charge
▪ Identify individuals and groups from various disciplinary domians who are actively engaged in curation for reproducibility
▪ Compare data and code curation practices across disciplinary domains

Output
Report that provides an overview of existing CURE practices, with detailed case studies that represent implementation of these practices by different stakeholder groups in different disciplinary contexts

Subgroup 3: CURE-FAIR Challenges

Aim
Describe the challenges of preparing and reusing materials required for computational reproducibility

Charge
▪ Collect information from various stakeholders (researchers, data curators, information professionals, IT, repositories, publishers, funders) about their challenges

Output
Report summarizing findings: See https://www.rd-alliance.org/group/cure-fair-wg/outcomes/challenges-curating-reproducible-and-fair-research-output

Subgroup 4: CURE-FAIR + RDA

Aim
Synthesize and bridge RDA outputs, recommendations, and WG/IG activities aligned with CURE-FAIR

Charge
▪ Assess the breadth of RDA outputs, recommendations, and WG/IG activities that support the curation and operationalization of computational reproducibility
▪ Review existing and upcoming RDA activities aligned with CURE-FAIR, as well as strategies supporting aligned adoption and overall value

Output
Report and adoption guide to support the implementation of CURE-FAIR definitions and practices

 

Discussion