BioCatHub, a platform for FAIR data acquisiton in biocatalysis

Introduction Reproducing experiments based on published experiments is challenging. The FAIR (Findable, Accessible, Interoperable, Reusable) data principles [1] are important tools to improve the reproducibility of experiments. Nevertheless, it can be a challenge for experimenters to implement FAIR-compliant research data management alongside their daily laboratory work. An increasing number of publishers, institutes and funding agencies demand data acquisition strategies based to the FAIR data principles which increases the pressure on the experimenter. Objectives To improve this, BioCatHub is being established. The main aim is to develop a research data management concept for biocatalysis and provide it as an easy-to-use web-interface customised, in particular, for experimenters in biocatalysis. Material and Methods The user interface is designed as wizard like structure and guides the experimenter through the different steps of an experimental procedure, collecting information describing the experiment (metadata) and measurement data. The collected data can be exported to the standardised file format EnzymeML (Enzyme Markup Language) [2] for local storage, or uploaded to the Zenodo platform [3], completing the data acquisition according to the FAIR data principles. Results The first version of BioCatHub went online recently and can be used to describe biocatalytic batch experiments based on the FAIR data principles (available at https://biocathub.net). Conclusion In this way, BioCatHub aims to simplify experimental data collection. It also provides a platform to collect negative experimental data as well, an underutilised source of valuable information in biocatalysis. In the future it will be important to extend the range of experimental procedures which can be described with BioCatHub (e.g. continuous or fed-batch processes). This target is planned to be realised in close cooperation with the biocatalysis community. References 1. Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. The FAIR Guiding Principles for scientific data management and stewardship. Scientific data. 2016;3:18–27. doi:10.1038/sdata.2016.18. 2. Range J, Halupczok C, Lohmann J, Swainston N, Kettner C, Bergmann FT, et al. EnzymeML - a data exchange format for biocatalysis and enzymology. The FEBS Journal 2021. doi:10.1111/febs.16318. 3. European Organization For Nuclear Research, OpenAIRE. Zenodo. 2013