Representing Semantified Biological Assays in the Open Research Knowledge Graph

Marco Anteghini*, Jennifer D’Souza, Vitor A.P. Martins dos Santos, Sören Auer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationDigital Libraries at Times of Massive Societal Transition - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings
EditorsEmi Ishita, Natalie Lee Pang, Lihong Zhou
PublisherSpringer
Pages89-98
Number of pages10
ISBN (Print)9783030644512
DOIs
Publication statusPublished - 28 Nov 2020
Event22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020 - Kyoto, Japan
Duration: 30 Nov 20201 Dec 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12504 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020
CountryJapan
CityKyoto
Period30/11/201/12/20

Keywords

  • Bioassays
  • Open Research Knowledge Graph
  • Open science graphs

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