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Abstract
Enzyme activity data for biocatalytic applications are currently often not annotated with standardized conditions and terms. This makes it extremely hard to retrieve, compare, and reuse enzymatic data. With advances in the fields of artificial intelligence (AI) and machine learning (ML), the automated usability of data in the form of machine‐readable annotations will play a crucial role for their success. It is becoming increasingly easy to retrieve complex data sets and extract relevant information; however, standardized data readability is a current limitation. In this contribution, we outline an iterative approach to develop standardized terms and create semantic relations (ontologies) to achieve this highly desirable goal of improving the discoverability, accessibility, interoperability, and reuse of digital resources in the field of biocatalysis.