Automatic Generation of Machine Readable Context Annotations for SPARQL Results

Ji-Woong Choi
2016 Journal of the Korea Society of Computer and Information  
In this paper, we propose an approach to generate machine readable context annotations for SPARQL Results. According to W3C Recommendations, the retrieved data from RDF or OWL data sources are represented in tabular form, in which each cell's data is described by only type and value. The simple query result form is generally useful, but it is not sufficient to explain the semantics of the data in query results. To explain the meaning of the data, appropriate annotations must be added to the
more » ... y results. In this paper, we generate the annotations from the basic graph patterns in user's queries. We could also manipulate the original queries to complete the annotations. The generated annotations are represented using the RDFa syntax in our study. The RDFa expressions in HTML are machine-understandable. We believe that our work will improve the trustworthiness of query results and contribute to distribute the data to meet the vision of the Semantic Web. ▸Keyword : Linked Open Data, SPARQL, RDFa, Provenance, Semantic Web I . In t r o duct i o n W3C 주도로 진행되고 있는 LOD(Linked Open Data) 프로젝 트의 확산으로 인해 시맨틱 웹 상에서 공개적으로 접근 가능한 다양한 분야의 데이터 셋이 빠르게 증가하고 있으며 이들 데이터 를 근간으로 한 활용 사례 또한 꾸준히 보고되고 있다[1,2]. 공개 데이터의 취득 수단은 RDF를 위한 질의 언어인 SPARQL 이다[3,4]. W3C의 표준문서 [5-7]에 따르면, SPARQL 결과 데 이터는 JSON, CSV, TSV, XML 포맷 중 하나로 표현될 수 있다.
doi:10.9708/jksci.2016.21.10.001 fatcat:j5huu4mrvjgaxm5jv3ol4rupxy