In the domain of biomedical research, findings having vital knowledge are buried in publications in the form of unstructured text. Users cannot manage all the available amount of information by themselves. In order to deal with this problem, fields like big data and semantic web are being extensively used for sorting and classifying it. Ontologies are tools that provide a way of sorting, classifying and describing large amounts of information. This paper presents an ontology on the breast cancer domain using UMLS as data source. Our ontology contains integrated entities from well-organized sources i.e. Unified Medical Language System (UMLS) which is published by National Library of Medicine (NLM) and contains 170 bio-medical vocabularies. At present the ontology comprises facts on relations and semantic types for 106 categories of breast cancer including 14 main types and 92 subtypes. In addition to this the ontology contains 101 categories of broader relations with 27092 records and 254 categories of more specific relations covered with 10250 records.
Knowledge and Data Science Research Centre (KDRC) 