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To whom does the “I” in FAIR belong? A cross-group discussion

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Agenda

  1. Welcome and icebreakers (5 min)
  2. Introduction to meeting and previous work (20 mins)
    1. FAIR Data Maturity Model (FDMM) WG introduction and outputs (10 min)
    2. Global Open Research Commons (GORC) IG and IM WG introduction and outputs (10 min)
  3. Presentation of topic and discussion on what interoperability means and how to aim for it (50 min)
    • How interoperability is defined and addressed by each group (15 min)
      1. FDMM WG
      2. GORC IG
  4. Panel discussion on how to achieve interoperability between commons (35 min)
  5. Discussion on moving forward together on shared and independent avenues of work (10 min)
  6. Next steps and conclusions (5 min)

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Icebreaker

Menti.com

�Code: 8224 5785

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Introduction to the RDA FAIR Data Maturity Model WG

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Context

rd-alliance.org @resdatall | @rda_europe | @RDA_US

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FAIR

The principles are NOT strict

  • Ambiguity
  • Wide range of interpretations of FAIRness

Different FAIR Assessment Frameworks

  • Different metrics
  • No comparison of results
  • No benchmark

SOLUTION is to bring together stakeholders to build on existing approaches and expertise

  • Set of core assessment criteria for FAIRness
  • FAIR data maturity model & toolset
  • FAIR data checklist
  • RDA recommendation

�Join the RDA Working Group: RDA WG web page

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Scope

rd-alliance.org @resdatall | @rda_europe | @RDA_US

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BUT the Working Group does NOT have the purpose to ...

  • develop yet-another-evaluation-method: the core criteria are intended to provide a common ‘language’ across evaluation approaches, not to be applied directly to datasets.
  • define how the core criteria need to be evaluated. The exact way to evaluate data based on the core criteria is up to the owners of the evaluation approaches, taking into account the requirements of their community
  • revise and re-design the FAIR principles

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History of the FAIR data maturity model WG

rd-alliance.org @resdatall | @rda_europe | @RDA_US

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Establishment of the WG

First draft of the model

Testing phase

Turning WG into maintenance mode

2019

2020

Discussing implications, uptake

2021-24

Survey FAIR assessments

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Process

www.rd-alliance.org @resdatall

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23/03/2020

Proposition

  • Indicators
  • Maturity levels

Consolidation

  • Indicators
  • Maturity levels

Discussion | Indicators

  • Validation (YES/NO)
  • Missing indicators

Discussion | Prioritisation

  • Approach to prioritisation
  • Priority levels
  • Survey

Testing

  • Pilot testing
  • Full testing

Discussion | Scoring

  • Approach to scoring

  • Scoping
  • Approach
  • Methodology
  • Landscaping exercise

Editorial team

Working group

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The Model

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FAIR data maturity model

rd-alliance.org @resdatall | @rda_europe | @RDA_US

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RDA recommendation

Evaluation mechanism

RDA Webpage

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Introduction to the RDA GORC IG and IM WG and outputs

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GORC Overview and Interoperability

https://www.rd-alliance.org/groups/gorc-international-model-wg

FAIR Data Maturity Model and GORC joint session at RDA Plenary 23

Andrew Treloar, Australian Research Data Commons

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Introduction - Global Open Research Commons (GORC)

GORC International Model WG

GORC IG

Roadmap

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Global Open Research Commons

  • Research Data Alliance Interest Group
  • Definitions and diagrams at https://doi.org/10.15497/RDA/00095

Can be used:

  • Retrospectively (SURF)
  • Prospectively (REASON, BioFair)
  • Analytically (interop between commons)

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Global Open Research Commons

  • Research Data Alliance Interest Group
  • Definitions and diagrams at https://doi.org/10.15497/RDA/00095

Can be used:

  • Retrospectively (SURF)
  • Prospectively (REASON, BioFair)
  • Analytically (interop between commons)

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Human Elements

Technical Elements

KPIs & Metrics

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12

speakers

150+

resources

35

meetings

5

plenary sessions

1

workshop

69

members

6

task groups

model

EOSC interoperability framework

FAIRsFAIR

RDA outputs

FAIR principles, related publications

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GORC IM WG outputs: Introduction, context, intent

  • Non-prescriptive guide
  • Spreadsheet container (for now)
  • Organized by IG essential elements, broken down into categories & subcategories
  • Extended description, examples, sources, consideration level.
  • Glossary
  • KPIs & metrics
  • Background information and intent
  • Detailed methodology
  • Narrative summary of model
  • Current and intended use of the model
  • Areas of future work

report

model

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Interoperability by RDA FAIR Data Maturity Model WG

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FAIR Data Maturity Model: specification and guidelines

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Interoperability indicators

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Maturity levels per indicator

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Feedback from adoptions

  • Over 20 adoptions captured
  • Several sessions sharing lessons learned
  • Interoperability is hard and requires discipline specific standards
  • Who sets those standards?
  • What is (machine readable) knowledge representation?
  • Who creates those FAIR vocabularies?
  • What are qualified references?

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Interoperability by GORC IG

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Types of Interoperability addressed in the GORC IM

Technical

Syntactic

Semantic

Organizational

Legal

Technical

Syntactic

Semantic

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Current thoughts on Interoperability

Caveat: This is very early thinking!

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Types of connectors

Technical:

  • The “easy” ones
  • “Hard” connectors
  • Existing solutions that can be drawn on/adapted

Social:

  • Much less easy
  • “Soft” connectors
  • Fewer existing solutions that can be drawn on/adapted
  • Not clear how to define interoperability for some of these elements
  • Lorentz workshop submission being evaluated

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Maturity levels and connectors

  • Not all commons are at the same level
  • Need a way for specifying backwards-compatible connectors between commons elements
  • Like the maturity level idea, but worry about the connotations of the word “maturity”
  • Something to investigate: International DataSpace Connectors have very granular usage control policy classes (21!)

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Panel Discussion

  • Javier Lopez Albacete, European Commission [virtual]
  • Gabriela Pino Chacon - University of Costa Rica [in person]
  • Danie Kinkade - Woods Hole Oceanographic Institution, USA [in person]
  • Mikiko Tanifuji, National Institute of Informatics, Japan [in person]

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Discussion

  1. Should this be driven bottom up or top down?
  2. Who is involved in building the interoperability within a commons?
  3. Who is involved in building the interoperability between commons?
  4. What does a system of interoperable commons look like?

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Next Steps

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