From 24 to 26 April 2020 the European Commission, led by the European Innovation Council, hosted a pan-European hackathon #EUvsVirus to connect civil society, innovators, partners and investors across Europe in order to develop innovative solutions for coronavirus-related challenges. Over 21,000 people from across the EU and beyond took part, with 2,150 solutions submitted in areas including health and life, business continuity, remote working and education, social and political cohesion, digital finance and other challenges. The TIB was involved in three projects.
Open Research Knowledge Graph, Big Data in Medicine and Scientific Knowledge
The "TIB ORKG" team around TIB Director Prof. Dr. Sören Auer and the Joint Lab of the TIB and the L3S Research Centre of Leibniz Universität Hannover leveraged the Open Research Knowledge Graph (ORKG) method to create a semantical comparison of the relevant bioassays in current COVID-19 research, aiming to fill the gap of lack of structured content-dependent approaches in querying bioassay information. This should further bolster the scholarly literature search for the COVID-19 associated bioassays and contribute to the faster development and application of appropriate bioassays in this domain. More information can be found in the TIB-Blog and in the project summary "Covid-19 Bioassays in the Open Research Knowledge Graph".
The project “Knowledge4COVID-19” aims to showcase the power of integrating disparate sources of knowledge to uncover patterns that may help to explain treatment effectiveness and the occurrence of adverse events. The team around Prof. (Univ. Simón Bolívar) Dr. Maria-Esther Vidal, head of the research group Scientific Data Management at TIB, joined efforts with the Software and Knowledge Engineering Laboratory (SKEL) at the National Centre for Scientific Research “Demokritos” from Greece: They created a Knowledge Graph from 52,000 scientific publications related toCOVID-19 and related drugs. On top of the knowledge graph, they have developed Artificial Intelligence methods to predict interactions and potential adverse effects of drugs suggested for the treatment of COVID-19. Such estimations are quintessential to make safety decisions related to new clinical trials. More information: "How Do Knowledge Graphs Contribute to Understanding COVID-19 Related Treatments?” and “Knowledge4COVID-19”
Scientific knowledge is one of the few tools we have in an otherwise near empty toolbox to fight COVID-19. Currently we are lacking other tools in: technology, medicines, healthcare, industry etc. Healthcare professionals and many other sectors are currently denied access to the world’s research knowledge to develop solutions. The goal of the project "ContentMine – scientific knowlegde for all" around Peter Murray-Rust of ContentMine, in which TIB employee Simon Worthington was also involved, was to build a universal warning system based on existing technical literature. To do this, the team read the full-text publications of all published research results on COVID-19 and indexed it for key facts using Wikidata. More information about “ContentMine – scientific knowledge for all”