Converting STKOS Metathesaurus to RDF Triples with R2RML
Wang Ying1, Wu Sizhu2()
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China 2Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing 100020, China
[Objective] This paper aims to convert STKOS Metathesaurus from records of relational database to RDF triples. [Methods] First, we defined the semantic schema of the STKOS based on their storage features and data characteristics. Then, we mapped the scientific terms, standard concepts, categories, as well as source concepts and terms with the help of R2RML. Finally, we converted the documents stored in relational database to RDF datasets with the R2RML parser. [Results] The proposed method could process STKOS metathesaurus automatically and generated 190 million RDF triples. All new records were stored in the Virtuoso database and could be queried with SPARQL. [Limitations] Predicates in the R2RML lacks flexibily, therefore, more complex data sets need to be splited and transformed first. [Conclusions] The proposed model shed light on future research on converting other relational database records or thesaurus to RDF datasets.
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