Representing Semantified Biological Assays in the Open Research Knowledge Graph
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Abstract (arXiv)
In 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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Sep 2020.
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Citing papers per year: 2021: 2; 2022: 1.
3 papers.
- 2021Automated Mining of Leaderboards for Empirical AI Researchcited by 16
- 2021Easy Semantification of Bioassayscited by 3
- 2022The Digitalization of Bioassays in the Open Research Knowledge Graphcited by 0
- 2022The Digitalization of Bioassays in the Open Research Knowledge Graph28 Mar 2022
- 2021Easy Semantification of Bioassays30 Nov 2021
- 2021Automated Mining of Leaderboards for Empirical AI Research31 Aug 2021