We want to create a catalog of medicines used to combat COVID-19, according to scientific literature, through the use of Artificial Intelligence and Citizen Science techniques.
- Data comes from NLP tools and is stored in SOLR databases
- Parallel defintion of the Ontology (not aligned with source data)
- Normalization steps (many multivalue columns)
- Flexible pipeline for continuos changes
- Website: https://kg.drugs4covid.oeg-upm.net/
- Data: 4 Solr Databases with data and NLP annotations from Papers (Parse to CSV)
- Endpoint: https://kg.drugs4covid.oeg-upm.net/sparql
- Mappings: https://github.com/oeg-upm/drugs4covid19-kg/tree/master/mappings
- Ontology: https://w3id.org/def/DRUGS4COVID19
- Output (using SDM-RDFizer):
