Fraunhofer SCAI launches a new COVID-19 knowledge space, building on tools developed during the AETIONOMY & PHAGO projects

On 23 April, Fraunhofer SCAI launched a new COVID-19 knowledge space which hosts tools for information extraction and literature mining, as well as SARS-CoV-2 disease models and information on chemical compounds and approved drugs that may be effective against SARS-CoV-2, the coronavirus that causes COVID-19.

The knowledge space is the result of a collaboration led by Prof. Martin Hofmann-Apitius at the Fraunhofer SCAI, with partners at Fraunhofer IME, Fraunhofer IAIS, ZB MED and the University of Luxembourg. Causality BioModels, an India-based spinout from Fraunhofer SCAI, was also involved in the development of this new resource.

Created in response to the huge volume of new publications on COVID-19 appearing each week, the knowledge space is designed to provide the scientific community with tools to mine these publications for novel insights on the transmission, aetiology and treatment of COVID-19, among other aspects.  Tools such as BiK>Mi (a key informatics development of the PHAGO project)  and SCAIView (which was developed during the AETIONOMY project) enable researchers to access and validate up-to-date knowledge on COVID-19, or perform semantic searches in large text collections from the scientific literature.  Alongside, researchers can navigate an interactive COVID-19 knowledge graph, a cause-and-effect network that provides a comprehensive overview of the mechanisms underlying COVID-19 pathophysiology.  The knowledge space also includes a Chemical Information Space, links to COVID-19 document collections, and a COVID-19 terminology, the basis for semantic interoperability in the COVID-19 knowledge discovery system.

The COVID-19 knowledge space can be accessed here: