Angebot 3: When FAIR Goes Wrong: Learning from Bad Examples in Electronic Lab Notebooks

What can we learn from a laboratory record that is not FAIR?

This interactive workshop takes a deliberately unconventional approach to FAIR Data Principles: instead of starting with best practices, we start with bad examples. Participants will examine selected examples of poorly documented entries in an electronic lab notebook (ELN) and work together to identify what makes these records difficult to understand, reuse, or interpret.

Using eLabFTW as a practical environment, the workshop focuses on questions that are relevant beyond any specific ELN system or research discipline: What information is missing? What would someone else need to understand or reuse this record? Which elements affect its Findability, Accessibility, Interoperability, and Reusability?

Participants will critically assess the examples from different disciplinary perspectives and then compare their observations with an existing template guide for creating FAIR laboratory records. This provides an opportunity not only to identify gaps in individual records, but also to reflect on whether existing guidance addresses the challenges researchers encounter in practice.

No prior knowledge of eLabFTW or the FAIR principles is required. The workshop is designed as a collaborative exercise in which different disciplinary perspectives are explicitly welcome. By turning bad examples into a starting point for discussion, we aim to make FAIR principles tangible, identify common documentation challenges, and explore practical ways to improve the quality and reusability of research records.

Join us in looking at what went wrong — and discover what it takes to make entries in eLabFTW FAIR.

The abstract was written with the help of AI (Chat AI,Qwen 3 30B A3B Instruct 2507)