This presentation was developed for the workshop “Challenges in Data Reusability”, jointly organized by FAIRMat, DAPHNE4NFDI, and the Helmholtz Metadata Collaboration (HMC) as part of Love Data Week 2026 (February 9, 2026). The workshop addressed key concepts related to research data reusability, including the differences between reuse, reproducibility, and replicability, and highlighted how the reproducibility crisis led to increased awareness around FAIR data principles (Findable, Accessible, Interoperable, Reusable). Particular emphasis was placed on Reusability as the ultimate goal of FAIR. Participants explored the practical foundations of reusable data, focusing on: The role of rich and well-structured metadata Persistent Identifiers (PIDs) README files as contextual metadata Data usage licenses, with special attention to Creative Commons licenses The importance of standards and controlled vocabularies to reduce ambiguity and enable interoperability The workshop included two connected hands-on challenges: Challenge 1 – Writing a README file:Participants were tasked with completing a README file in a way that would allow someone who cannot contact the data creator to understand and reuse the dataset. The exercise emphasized completeness, clarity, and structured metadata documentation. Challenge 2 – Reusing a dataset:In the second challenge, participants assumed the role of data reusers. Using a dataset and a README prepared by another group, they answered analytical and licensing-related questions. This exercise demonstrated how metadata quality and licensing decisions directly affect the feasibility of reuse.
ÖZKAN et al. (Thu,) studied this question.