The proliferation of biological research data generated and shared openly online is of huge benefit to the scientific community, but there are often significant challenges to overcome before it can be integrated from different sources and re-used to gain new knowledge. This paper introduces BioGrakn, which is a graph-based deductive data- base, combining the power of knowledge graphs and machine reason- ing. BioGrakn illustrates how data can be aggregated and integrated, modelled in all its complexity and contextual specificity, and extended as needed. Built upon GRAKN.AI, it provides an integrated, intelligent database for researchers handling complex data.
BioGrakn: A Knowledge Graph-Based Semantic Database for Biomedical Sciences
Antonio Messina;Alfonso Urso
2017
Abstract
The proliferation of biological research data generated and shared openly online is of huge benefit to the scientific community, but there are often significant challenges to overcome before it can be integrated from different sources and re-used to gain new knowledge. This paper introduces BioGrakn, which is a graph-based deductive data- base, combining the power of knowledge graphs and machine reason- ing. BioGrakn illustrates how data can be aggregated and integrated, modelled in all its complexity and contextual specificity, and extended as needed. Built upon GRAKN.AI, it provides an integrated, intelligent database for researchers handling complex data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
