The proposed session will bring together people interested in the RDA FAIR Data Maturity Model (FDMM) and other FAIR assessment approaches, to discuss the FAIR DMM model implementation and its use in real life. In particular, we are focused on those participants who are in early stages and are interested in trying the FAIR DMM as a future tool for FAIR assessment and want to understand the basic concept of the FAIR DMM as preparation for their selection process. This can be those considering incorporating the FDMM in existing services or using the FAIR DMM and its criteria itself.
This session is intended to offer opportunity to existing implementers to share their lessons and for interested future users to ask their questions and raise their initial concerns from different domains.
We are also interested to get feedback about the interoperability as a goal: Is the target to achieve inter-domain or within-domain interoperability.
Collaborative session notes: https://docs.google.com/document/d/1-waZK0XE_9ttcrLMN3JUXaM083QbIxwiydkr1Q0OuE8/edit?usp=sharing
[5 min] Welcome, objectives of the meeting
[10 min] Keith Russell (ARDC) - implemention in practice
[10 min] Frances Lightsom (USGS) - implementation in practice
[55 min] Roundtable - speakers and FAIR Data Maturity Model (FDMM) implementers
Andreas Czerniak - OpenAIRE validator
Erik Schultes - Go-FAIR
Fran Lightsom - USGS
Ilona van Stein - Metrics and Certification Task Force of the EOSC FAIR Working Group
Keith Russell - ARDC
Rob Hooft - DTLS
Robert Huber - FAIRsFAIR tools
How to place the FDMM in the larger ecosystem?
How can the FDMM be used to implement FAIR?
How can the FDMM and your FAIR assessment method enable culture change around data and software sharing?
What do you think is missing from the FDMM for your implementation, what are obstacles/constraints in your implementation?
[10 min] Action items and Next steps
Researchers, data service owners, funders and infrastructures from different scientific and research disciplines, the industry and public sector, who are active and/or interested in the FAIR data principles and in particular in assessment criteria and methodologies for evaluating their real-life uptake and implementation level.
We are interested in meeting the newcomers and those who are starting their FAIR journey, the representatives of the Implementing methods across regions, and the use case owners who offered to share their experience.
FAIR Data Maturity Group Working Group
The RDA FAIR Data Maturity Group was established at the end of 2018 with the objective to bring together stakeholders from different scientific and research disciplines, the industry and public sector, who are active and/or interested in the FAIR data principles and in particular in assessment criteria and methodologies for evaluating their real-life uptake and implementation level. The Working Group completed an RDA Recommendation, a common set of core assessment criteria for FAIRness and a generic and expandable self-assessment model for measuring the maturity level of a dataset. The group has over 250 members representing a wide range of disciplines and regions around the world.
The Working Group worked in 2019 and the first half of 2020 to develop an RDA Recommendation on assessment of FAIRness in research data. The RDA Recommendation FAIR Data Maturity Model: specification and guidelines was published on 8 June 2020 (https://doi.org/10.15497/RDA00050). Since then, the Working Group has entered maintenance mode and is currently developing a work plan for the next years.