Linked Open Data (LOD) in life sciences is about a movement dealing with an interconnected set of Big Data from clinical records, trials and pharmacologic interventions to next generation sequencing and proteomics. The combination of these evidence is a prerequisite for biomedical bibliometrics, conduction of systematic reviews and meta-analyses, evidence-based medicine and precision medicine. Therefore, we collected the BioPortal subdomain life sciences LOD datasets triples and links from the LOD Cloud diagram and old.datahub.io repository to explore their connections to the three top ontologies describing clinical, pharmacological and molecular biology information, SNOMED CT, RxNORM and GO respectively. We found that 96% of the datasets share links with SNOMED CT, 24% with RxNORM and 31.5% with GO. However, the datasets that share links with both RxNORM and GO are only 3.5%. Our data suggest the need of enrichment of life science LOD datasets with connections between pharmacology and molecular biology.
Semantic web, Linked Data, Biomedicine, Life Sciences, Ontologies, Bibliometrics, Evidence-based medicine, Precision medicine
Cite this paper
Artemis Chaleplioglou, Sozon Papavlasopoulos, Marios Poulos. (2018) Life Sciences Linked Open Data Datasets Connections to SNOMED CT, RxNORM & GO. International Journal of Computers, 3, 171-176
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