Door Paolo Rossini, Informatiespecialist & Data Steward bij Operatie Nachtwacht

When people think of museums, they often picture paintings, sculptures, and artifacts—not terabytes of research data. Yet behind the scenes, cultural heritage institutions like the Rijksmuseum are generating vast and complex datasets every day. From high-resolution imaging and chemical analyses to historical documentation, these data are essential for preserving and understanding our shared heritage. But how do we make them FAIR—Findable, Accessible, Interoperable, and Reusable?

A Data Steward’s Perspective

As a data steward at the Rijksmuseum, I’ve had the privilege of working on one of the most ambitious projects in the museum world: Operation Night Watch, the multi-year conservation and research initiative focused on Rembrandt’s masterpiece. This project is not only about safeguarding a painting; it’s about building a sustainable data ecosystem that supports open science and interdisciplinary collaboration.

Why FAIR Matters in Museums

FAIR principles have become a cornerstone of responsible research data management in science, but their application in museums is still emerging. Cultural heritage data pose unique challenges: they are heterogeneous, often tied to physical objects, and governed by complex legal and ethical constraints. Implementing FAIR in this context requires more than technical solutions—it demands cultural change, collaboration, and creativity.

My Role as a Data Steward

In Operation Night Watch, my role was to bridge the gap between researchers and infrastructure. This meant:

• Translating FAIR principles into practical steps for conservators, imaging specialists, and art historians.

• Creating and iterating Data Management Plans (DMPs)—not as static documents, but as living tools that evolve with the project.

• Supporting data curation and documentation, from designing folder structures and file naming conventions to building metadata catalogues for thousands of technical images.

• Advising on licensing and access control, ensuring that openness is balanced with legal and ethical considerations.

One of the most important lessons learned was fostering a culture of shared responsibility. FAIRification is not something a data steward can do alone; it requires active engagement from everyone involved. And none of this would have been possible without the incredible work of my colleagues from the Collection Information & Archive (CIA) department, who laid the foundations by drafting guidelines, formalizing work agreements, and delivering the essential training on research data management.

Other Lessons Learned

• Start early, iterate often. Embedding FAIR principles from the beginning saves time and reduces friction later.

• Balance idealism with pragmatism. The perfect workflow rarely exists; flexibility is key.

• Invest in people, not just technology. Tools matter, but awareness and skills are what make FAIR sustainable.

Looking Ahead

FAIRification is not a one-time achievement—it’s an ongoing process. At the Rijksmuseum, we’re exploring next steps like linking metadata to external knowledge graphs (e.g., Wikidata) and developing an infrastructure aligned with best practices in research data management. These innovations will help us move from FAIR data to truly open, connected, and reusable cultural heritage information.

For me, being a data steward is about more than managing files—it’s about enabling research that lasts, fostering transparency, and ensuring that the stories behind our cultural treasures remain accessible for generations to come.

Further Reading

Wilkinson, M. D. et al., ‘The FAIR Guiding Principles for scientific data management and stewardship’, Scientific Data 3 (2016), 160018, https://doi.org/10.1038/sdata.2016.18.