The Research Data Alliance (RDA) held their 18th Plenary in early November over a week’s span or four days (no Fridays, weekends, or Mondays – a picture perfect work schedule in my mind). This was my first RDA Plenary thanks to the DCN (financial support) and the pandemic (virtual access). One of the things I have appreciated about the pandemic is how institutions and organizations have done the work to go online to connect with their users/patrons/members.
The RDA Plenary was full of presentation/breakout session formats that I was not familiar with and made me a bit nervous. Birds of a Feather (BoF), Interest Groups (IG), and Working Groups (WG). Huh? What if I just wanted to listen? What if I lacked confidence to participate? Am I being judged for not turning on my camera? I want to let you all know that I did a lot of listening and so did others. I participated when I felt like it and so did others. No one judged me (that I am aware of) when I had my camera on or off.
The CURE- FAIR WG’s session “Connecting the Dots on Curating for FAIR and Reproducible Research” introduced attendees to the working group’s charter, shared their anticipated deliverables, and provided updates on the four sub-groups’ progress. At the end of the session, as advertised, was an opportunity for attendees to participate and engage with “10 Curation for Reproducible and FAIR Things.”
The overall goal of the WG is to “establish standards-based guidelines for curation of reproducible and FAIR data and code” that is “informed by an examination of current curation practices and their alignment with FAIR principles” to form a “framework for implementing effective curation workflows for publishing FAIR data and code that support reproducibility” (WG charter)
I was pleased to see the use of subgroups to manage the work. Everything seems SO overwhelming in the world that it is so easy to get stuck before you even start. I am happy to see that while volunteer, these types of professional groups are attempting to distribute the work. The sub groups of the WG are: 1) CURE-FAIR Definitions, 2) CURE-FAIR Practices, 3) CURE-FAIR Challenges, and 4) CURE-FAIR + RDA
- The CURE-FAIR Definitions subgroup’s goal is to help provide a broad understanding of what it means to curate research artifacts for the purposes of sporting research reproducibility in the context of FAIR principles. The subgroup developed a Zotero library to collect literature about this and encourage you to reach out if you have additions. You can do that by visiting their contributor guide which also shares the Zotero library.
- The CURE-FAIR Practices subgroup’s goal is to explore curation for reproducibility practices as they are implemented in various disciplinary domains and by different stakeholders groups. To get this work going, the group developed a CURE-FAIR Implementer Survey for the community to share how they have implemented data curation tools, services or workflows to support computational reproducibility.
- The CURE-FAIR Challenges subgroup’s goal is to describe the challenges of preparing and reusing materials required for computational reproducibility. The group collected information from stakeholders such has researchers, publishers, data professionals, etc. about their challenges. The resulting output is a report called Challenges of Curating for Reproducible and FAIR Research Output
- The CURE-FAIR + RDA subgroup’s goal is to synthesize and bridge RDA outputs, recommendations, and WG/IG activities aligned with CURE-FAIR. The subgroup gathered details from existing activities and working relevant references into recommendations. Some of those recommendations are: FAIR4RS WG, Publishing Data Workflows WG, Attribution Metadata WG, and FAIR Data Maturity Model WG.
10 CURE-FAIR Things
The session wrapped up by introducing 10 CURE-FAIR Things which is a document that includes standards-based guidelines for CURE-FAIR best practices. The 10 CURE- FAIR Things are: Completeness, Organization, Economy, Transparency, Documentation, Accessibility, Provenance, Machine-readable metadata, Automation, and Maintenance. After the introduction, attendees broke up into a couple of groups to work in the document, suggesting in Thing 8 – Machine – Readable metadata. The WG’s hope is that it will serve as a “starting point for the development of curatorial guidelines tailored to the specific concerns of the social sciences community, other domains, and disciplines, and to the particular curatorial concerns and requirements of an archive of publisher.” It was also mentioned that while this guide may be more used in the social sciences, there is interest in expanding to other disciplines. The intended audience for the guide is twofold: “1) Data curators and information professionals who are charged with verifying that a computation can be executed and can reproduce prespecified results and 2) Researchers, publishers, editors, reviewers, and others who have a stake in creating, using, sharing publishing, or preserving reproducible research.”
So now what?
The CURE-FAIR WG has a few calls for participation to share with you all:
- Join the “Curating for Reproducible FAIR Data and Code” (CURE-FAIR) Working Group: https://www.rd-alliance.org/groups/cure-fair-wg
- Contribute to “10 Curation for Reproducible and FAIR Things”: https://docs.google.com/document/d/14A1sqdxhGAsFlPoyHUglrS89rcLY5aP_xizO2ZckcKA/edit?usp=sharing
- Submit a CURE (curating for reproducibility) resource (e.g., article, website, report): https://forms.gle/DFJ21YJpcaPgtW9W8
- Tell the WG about your CURE implementation: https://bit.ly/2OWWryg
Attending RDA virtually was a great experience. I hope one day to attend IRL and meet all the wonderful people that lift up the community.
Disclosures: The Data Curation Network paid the author’s RDA Plenary 18 registration fee and the author is a Data CuRe Fellow.