Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.Anteghini, MarcoD'Souza, JenniferMartins dos Santos, Vitor A.P.Auer, SörenIshita, EmiPang, Natalie Lee SanZhou, Lihong2021-06-042021-06-042020https://oa.tib.eu/renate/handle/123456789/6177https://doi.org/10.34657/5224In the biotechnology and biomedical domains, recent text mining efforts advocate for machine-interpretable, and preferably, semantified, documentation formats of laboratory processes. This includes wet-lab protocols, (in)organic materials synthesis reactions, genetic manipulations and procedures for faster computer-mediated analysis and predictions. Herein, we present our work on the representation of semantified bioassays in the Open Research Knowledge Graph (ORKG). In particular, we describe a semantification system work-in-progress to generate, automatically and quickly, the critical semantified bioassay data mass needed to foster a consistent user audience to adopt the ORKG for recording their bioassays and facilitate the organisation of research, according to FAIR principles.eng020BioassaysOpen Research Knowledge GraphOpen science graphsBookPartKonferenzschrift