Speakers
Description
As global communities continue to adopt the FAIR Principles, many organizations face the challenge of not just FAIRifying individual datasets, but entire ecosystems of data repositories and services. The many tools and assessments developed for FAIR tend to be customized to a particular data architecture, especially data organized in a file with a DOI and listed on a website. The National Institute of Allergy and Infectious Diseases (NIAID), an Institute within the US National Institutes of Health, manages a data landscape that includes infectious, allergic, and immunologic data. NIAID data has been at the forefront of research and therapeutics for today’s biggest public health challenges, and the NIAID Data Landscaping and FAIRification project targets increasing the discovery and reuse of these data. With this diversity of topic, use, and audience, assessing NIAID data resources for FAIRness brings a host of challenges: diverse data architectures, varying levels of entity management, declaration, and resolution, and data that has been collected over many time scales—decades in some cases. This short presentation will describe the project undertaken by GO FAIR US and partners including highlights related to:
- Customized FAIR assessment instruments
- Evaluating record-based repositories (in addition to file-based ones)
- Assessing individual data resources’ progress towards a common approach
- Using Impact assessment to drive adoption of community- and standards-based metadata and PIDs
- Increasing the value and use of citations for all types of data products
- Accommodating social and project constraints, needs, and opportunities
The approach described uses a novel, stakeholder-informed method for assessing how well data repositories meet the FAIR Principles—developed and applied by GO FAIR US with support from GO FAIR Foundation with close partnership between GO FAIR US, NIAID, and the National Center for Atmospheric Research6,7. The method builds on and extends prior impactful work1,3 from FAIRsFAIR2, the RDA Data Maturity Model Working Group4, the National Science Foundation’s EarthCube5, GO FAIR Foundation’s methods including FAIR Implementation Profiles, and others.
For this project we designed tailored questionnaires and interviews for different repository roles (managers, technical staff, data depositors, data users) to provide a multi-dimensional view of FAIR practices. The assessment products combine desk-based research and structured templates like FAIR Implementation Profiles to create a detailed FAIR baseline for each repository—including metadata practices, technical infrastructure, and governance. This addresses the limitations of automated tools when assessing complex or secure repositories, and offers a qualitative, human-centered alternative. The assessment is then used to produce targeted FAIRification strategies that align with a repository’s goals, constraints, and domain-specific practices. This method enables comparative analysis across multiple repositories and informs broader strategic planning for FAIR implementation, while supporting repository ownership and buy-in.
References:
European Commission: Directorate-General for Research and Innovation, European Research Data Landscape – Final report, Publications Office of the European Union, 2022, https://data.europa.eu/doi/10.2777/3648
FAIRsFAIR’s “Fostering FAIR Data Practices in Europe” project documentation, https://cordis.europa.eu/project/id/831558
Mathers, B.J., L’Hours, H., Increasing the Reuse of Data through FAIR-enabling the Certification of Trustworthy Digital Repositories, https://doi.org/10.5334/dsj-2020-041 which explores the alignment of the FAIR Data Principles with the CoreTrustSeal Trustworthy Digital Requirements
Recommendations from a Research Data Alliance Data Maturity Model Working Group, which identifies FAIR data maturity model indicators (Bahim et al., 2020)
Questions that EarthCube Office staff used to interview EarthCube project leads about the organization’s impact (Stocks and Evans, 2022)
“GO FAIR US awarded a NIAID FAIR data and ecosystem contract by Frederick National Laboratory for Cancer Research.” GO FAIR US, Dec. 2023. Press release. https://www.gofair.us/post/go-fair-us-awarded-a-niaid-fair-data-and-ecosystem-contract-by-frederick-national-laboratory-for-can
“Data Landscaping Project Aims to Make NIAID Data More Accessible, Promote Reuse”. Data Science Dispatch, 5 June 2024. https://www.niaid.nih.gov/research/data-landscaping-project
This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. 75N91019D00024. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.
