Currently, kinetic parameters and corresponding information about the reactions, enzymes, and experimental conditions are extracted and annotated manually from scientific publications and inserted into databases such as SABIO-RK or BRENDA to structure and standardise the data. Missing information such as unambiguous external identifiers is added manually by database curators. As a first step for the standardised reporting of enzyme function data, the enzymology and biocatalysis community has established the Standards for Reporting Enzymology Data (STRENDA) Guidelines, which provide the minimum information necessary to describe assay conditions and enzyme activity data . Currently, more than 55 international biochemistry journals have included adherence to the STRENDA Guidelines in their instructions for authors reporting enzymology data. STRENDA DB has been established as a public database to support authors checking the completeness of their data upon submission of their manuscript and to provide public access to data on reaction conditions and kinetic parameters of an experiment . However, the upload of data is performed manually via a graphical user interface, and the process from data acquisition to kinetic modelling and publication is still time consuming and error prone. Most importantly, original data such as the measured time course of substrate and product concentrations is not reported or has to be extracted from figures, thus preventing the reuse of original data for kinetic modelling. Not only is published data incomplete and inaccessible, but also unpublished research data and metadata are stored by research group members with insufficient documentation and annotation. In addition, the current data management prevents researchers from upscaling their experimental designs to high-throughput biocatalytic approaches by using pipetting robots or flow reactors , and hinders the comprehensive study of the multidimensional parameter space of biocatalytic reactions.