Enhancing FAIR Principles in Research Software: Ontology and Metadata Annotations for the Energy System Model AMIRIS

Abstract

While significant progress has been made in defining the theoretical requirements for FAIR data, examples of fully FAIR implementations in mature energy system models remain scarce. This presentation extends the FAIR principles to research software, focusing on automating the generation of FAIR-compliant output data by annotating variables with ontology terms. We show an actual transformation of such a model, AMIRIS, from a closed-source software using proprietary data without metadata into an open source software, employing open data, adhering to FAIR principles throughout.