Investigating the Landscape of Ontologies for Catalysis Research Data Management

Abstract

This work provides a survey of ontologies for catalysis research to improve the findability, accessibility, interoperability, and reusability (FAIRness) of research data. Applying tools that are commonly used by lab scientists, ontologies relevant to catalysis research are classified in a simple, well formatted spreadsheet template (Excel). This enables a scientist and domain expert without programming skills to evaluate a certain ontology. The entries of this template are then processed and visualized through automated creation of markdown files on GitHub using Python scripts. Furthermore, ontology mapping by searching for similar pairs of classes across different ontologies is performed, using the outcome of the ontology classification. This work contributes to the development of ontologies for catalysis research, facilitating better data integration and knowledge sharing while reusing existing semantic artefacts.