GOALS:
The workshop will expose participants to best practices and guidelines to make data FAIR and walk them through step-by-step recipes to make research data findable, accessible, interoperable, and reusable.
OUTCOMES:
Participants will get hands-on experience of FAIR planning and adoption using example research datasets. Working in groups, participants will be able to experience the FAIRification journey and ask questions of the FAIR community experts. Participants will leave with an understanding of the FAIR framework, ability to conduct a FAIR assessment, and tools to improve the FAIRness of their research data.
AUDIENCE and PREREQUISITES:
The workshop will serve those seeking to deliver value from data management best practices at all stages of their "FAIRification" journey. No prerequisites necessary to register for this workshop.
AGENDA:
9:00 am Organizer's Welcome Remarks
9:05 am Chairperson's Remarks
Ishwar Chandramouliswaran, Program Director, Office of Data Science Strategy, NIH
Nick Lynch, PhD, Founder & CTO, Curlew Research; Member, FAIRplus Consortium
9:15 am Short/Lightning Talks—Part 1
- Short Talk 1: FAIR Assessment—Overview of Community Activities
Susanna-Assunta Sansone, PhD, Professor of Data Readiness, Department of Engineering Science; Academic Lead for Research Practice, University of Oxford
- Short Talk 2: Pistoia Alliance's FAIR Maturity Matrix
Giovanni Nisato, PhD, Consultant, Project Manager FAIR implementation, Pistoia Alliance
At any given time, organizations are at varying stages of their FAIR implementation journeys, making it challenging to benchmark the level of FAIRness achieved. While several FAIR data maturity models and metrics exist, until recently, there was no comprehensive maturity assessment model tailored for implementing FAIR data principles at the organizational level in life sciences. To address this gap, the Pistoia Alliance FAIR Implementation Project developed the FAIR Maturity Matrix, a framework collaboratively designed by over 20 experts from leading pharmaceutical and life science organizations, as well as consultancies.
The matrix identifies seven dimensions critical to FAIR implementation: Data, Leadership, Strategy, Roles, Processes, Knowledge, Tools, and Infrastructure. These dimensions are complementary rather than hierarchical, ensuring flexibility in application. The model defines six maturity levels:
- 0: Life is unFAIR: Lack of awareness.
- 1: Started the FAIR journey: Awareness initiated.
- 2: Getting FAIR: Pilot implementations underway.
- 3: Pretty FAIR: Transitioning to good and best practices.
- 4: Really FAIR: Reflecting best industry practices to date.
- 5: FAIRest of them all: Aspirational goals yet to be realized.
Descriptive rather than prescriptive, the FAIR Maturity Matrix equips stakeholders with a consistent framework to assess, qualify, and measure organizational progress. It supports effective management of advancements toward FAIR compliance, enables benchmarking both across organizations and within internal departments, and fosters a shared understanding of FAIR maturity. The first version of the FAIR Maturity Matrix was released in March 2024 and is accessible at fairmm.pistoiaalliance.org.
- Short Talk 3: FAIRification Journey Using the FAIRification Framework
Nick Juty, PhD, Senior Research Technology Manager, eScience Lab, University of Manchester
- Short Talk 4: RDMKit
Munazah Andrabi, PhD, Data & Community Manager, The University of Manchester - Short Talk 5: FAIR CookBook
Vassilios Ioannidis, PhD, Team Lead FAIR Data Management Unit, Vital-IT, Swiss Institute of Bioinformatics
10:15 am Networking Coffee Break
10:30 am Group Activity—Part 2
Activity Supporters: Navjot Juty, Munaza Andrabi, Vassilios Ioannidis, David Tanenbaum, and Andrew Hasley
Part 2 begins with a brief overview of instructions for the activity, followed by a break to facilitate group formation and discussions. Participants will then engage in a hands-on collaborative session of FAIRification group work, applying best practices to real-world data scenarios. Afterward, a break allows teams to come back together and prepare for report-outs. The workshop concludes with a dynamic session where groups present their findings and engage in open discussions, fostering knowledge exchange and actionable insights.
11:55 am Closing Remarks
12:00 pm End of Workshop