Prototype Implementation of SPARQL Builder for Life-science Databases by Intelligent Schema Analysis on RDF datasets

Metadata publication in accordance with the semantic web as a database is a trend for providing and integrating various life-science data. These metadata are published as SPARQL endpoints, a standardised API for RDF datasets. As life-science data are very widely diverse and described using various ontologies and data classes, writing an efficient SPARQL query for SPARQL endpoints is difficult for biologists. To address this problem, we propose an intelligent SPARQL query builder that enables users to build a query without knowledge of SPARQL or the data schema. We have developed a prototype version of the SPARQL builder accessible via users’ web browsers. The system crawls SPARQL endpoints in advance to analyse the data schema of large amounts of data, and the resultant crawled data are stored as RDF datasets. This paper focuses on the implementation including the system overview, and the data structure of the resultant crawled data.