Semantic data modeling for interoperable hydrogen research infrastructures

The emergence of hydrogen as an important energy vector has been evi dently noted from the past few years. This brings in the importance of research infrastructures dedicated towards hydrogen to further enhance the deployment of this energy vector. These infrastructures, consisting of multi ple interconnected units, produce significant amounts of heterogeneous data whose effective utilisation requires a structured and well-defined data man agement strategy. This work is focused on implementing a FAIR-by-design approach for handling data obtained from a hydrogen smart laboratory which is still under construction and is projected to be completed in 2027. This approach of setting the base and structure for data procurement will save ample amount of time and resources in comparison to future FAIRification of data. Moreoever, this approach facilitates for a modular design, thus al lowing us to integrate further counterparts and acquire structured data in an elaborated platform. The work consists of three steps following this prin ciple, which involves drafting a DMP, designing a conceptual data model, and then developing a layered, hierarchical ontology based on this concep tual model. The resulting ontology, named HydLab, has been developed in compliance with the FAIR principles, with the additional objective of estab lishing a modular methodology that enables the extension and adaptation of the model to other hydrogen research infrastructures.