Insights from the Seminar FAIR data infrastructures for the SSH

5 March 2025

Written by Angelica Maineri (ODISSEI Data Manager).

The Challenge of FAIR Implementation in SSH

On February 13th, data providers, RDM experts, and infrastructure providers gathered in Utrecht for the “FAIR Data Infrastructures for SSH” seminar. [1] Organized by the PDI-SSH project “Building a FAIR Expertise Hub for the Social Sciences” and ODISSEI, this event tackled a crucial question: How can we overcome bottlenecks and effectively support FAIR implementation in the Social Sciences and Humanities (SSH) in the Netherlands?

Key Findings from the Dutch SSH Community

Through collecting FAIR Implementation Profiles (FIPs [2]) from various SSH data providers, the FAIR Expertise Hub gained a better understanding of the status of FAIR Implementation in the domain, and uncovered two bottlenecks:

  1. Infrastructure Constraints: Many SSH providers, especially those handling sensitive data, rely on existing platforms to publish their (meta)data. By doing so, they often automatically inherit FAIR implementation choices from the infrastructure provider who picked the platform. These constraints concern, for instance, metadata schemas, persistent identifiers (PIDs), and licensing options. This creates a need for:
    • Making these constraints explicit;
    • Validating these choices as appropriate for both data providers and users.
  2. Semantic Resource Gaps: There’s a significant shortage of FAIR semantic resources (like controlled vocabularies and ontologies) for SSH data. This gap severely impacts the Interoperability aspect of FAIR principles, limiting the potential for data linkage across different sources and hindering innovative research opportunities.

Real-World FAIR Implementation: Three Case Studies

Case 1: Enhancing Cohort Data Discovery

Otto Lange and Dorien Huijser (Utrecht University) from the Consortium Individual Development presented their metadata catalogue for cohort studies. Their project demonstrates excellent FAIR implementation through:

  • Creating a single access point for numerous datasets
  • Extensive metadata harmonization
  • Developing controlled vocabularies to improve discovery and interoperability

Read more about the CID catalogue at [3].

Case 2: Preserving Socio-Historical Data

Rick Mourits (International Institute of Social History) emphasized FAIR implementation as a continuous community effort to prevent “dark data” in socio-economic history. Using a powerful analogy, he described FAIR implementation as “building bridges between islands” and offered practical starting points for data providers willing to start their FAIR implementation journey.

Case 3: Sharing Sensitive Company Data

Rutger Schilpzand (Utrecht University) from FIRMBACKBONE outlined their approach to sharing sensitive company data in a FAIR-compliant manner. The FIRMBACKBONE team leverages FAIR principles to make restricted-access datasets more accessible while balancing privacy concerns. They highlighted FIPs as valuable tools for streamlining FAIR implementation efforts.

Workshop Highlights: Addressing Key Challenges

Workshop 1: FAIR Data (and) Infrastructures

Lucas van der Meer (ODISSEI) and Ahmad Hesam (SURF) led participants through an exercise to evaluate their current FAIR implementation status. This activity helped participants reflect on their progress while providing valuable feedback to the FAIR Expertise Hub and ODISSEI teams about:

  • The appropriateness of current FAIR implementation options via the ODISSEI infrastructure
  • Gaps and needs requiring further attention

The workshop concluded with practical instructions on using SANE (Secure Analytics Environment) for sharing sensitive data.

Workshop 2: Tackling the Semantic Resource Shortage

Angelica Maineri (FAIR Hub and ODISSEI) facilitated a discussion on engaging researchers to address the shortage of semantic resources. The group reached consensus that the gap is smaller than perceived, as social scientists already do significant conceptual work. However, three implementation challenges emerged:

  • Confusion around terminology
  • Need for clear, practical guidelines on reusing and adapting semantic resources
  • Insufficient recognition and rewards for publishing/reusing semantic resources

These challenges will be addressed by workshop participants within the SSHOC-NL context.

Conclusion: The Layered Nature of FAIR Implementation

A key insight from the closing discussion, chaired by Tom Emery (ODISSEI), was that FAIR implementation is layered.  While some aspects are now relatively straightforward (like publishing data in registries with PIDs, metadata schemas, and licenses), the deeper aspects of Interoperability and Reusability remain challenging.

These more complex layers require active engagement from research communities—infrastructure providers cannot address them alone. Building truly FAIR data ecosystems in the social sciences demands ongoing collaboration between technical experts and domain researchers.

References

[1] This OSF page collects all the slides from the day.

[2] Read more on FIPs on https://odissei-data.nl/2022/12/14/fair-in-the-social-sciences/

[3] Read more details on https://odissei-data.nl/2025/02/11/increasing-the-visibility-and-fairness-of-child-development-data/

Image by TSD Studio on Unsplash