A Linked Data Application for Harmonizing Heterogeneous Biomedical Information

In the biomedical field, there is an ever-increasing number of large, fragmented, and isolated data sources stored in databases ontologies that use heterogeneous formats poorly integrated schemes. Researchers healthcare professionals find it extremely difficult to master this huge amount extract relevant information. work, we propose a linked approach, based on multilayer networks semantic Web standards, capable integrating harmonizing several datasets with different schemas semi-structured through multi-model database providing polyglot persistence. The domain chosen concerns analysis aggregation available neuroendocrine neoplasms (NENs), relatively rare type neoplasm. Integrated information includes twelve public including RDF, CSV, TSV, SQL, OWL, OBO. proposed model consists six interconnected layers representing, respectively, disease, related phenotypic alterations, affected genes, biological processes, molecular functions, involved human tissues, drugs compounds show documented interactions them. defined scheme extends existing three-layer covering subset mentioned aspects. A client–server application was also developed browse search for model. main challenges work concern complexity domain, syntactic heterogeneity datasets, organization Unlike works, have been adopted organize manageable stratified structure, without need change original but by transforming their “on fly” respond user requests.