Using FAIR Digital Objects for a Harmonized Representation of NMR Spectroscopy Data

The growing diversity and complexity of research data introduce substantial challenges, especially regarding the findability, accessibility, interoperability, and reusability of data.
To address these challenges, the FAIR principles were established, guiding best practices for sustainable and efficient management of research data.
FAIR Digital Objects (FAIR-DOs) embody these principles, aiming to provide common mechanisms to enable machine-actionable, persistent, and harmonized representation of (meta)data beyond the borders of data spaces.

In this work, we apply FAIR-DOs on top of two repositories containing nuclear magnetic resonance (NMR) spectroscopy data.
For that, we automatically extracted selected domain-specific metadata from the nmrXiv.org and Chemotion.net repositories and transformed them into meaningful and well-typed information that can be stored within FAIR-DO information records.
We developed heuristics to ensure the quality of the information inside our FAIR-DOs by, e.g., finding and using terms with a terminology service, using SPDX license identifiers, and ensuring authors are referenced by their ORCiD.
Additionally, we connected FAIR-DOs based on the metadata provided in the repositories.
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Totaling around 27 thousand FAIR-DOs, we provide an extensive use-case of FAIR-DOs and the technology framework enabling them.
We additionally developed a user-friendly search interface, based on well-established and highly customizable tooling, that allows powerful filtering and sorting as well as graph-based inspection of our FAIR-DOs and their relations.
Our work enables researchers from the NFFA Europe Pilot and NFDI4Chem to uniformly explore resources from multiple data sources with FAIR-DOs as a harmonized representation.