Querying Fuzzy Spatiotemporal RDF Data Using R2RML Mappings

Abstract

With the development of Internet technology, information management has shown a spurt of growth. In real-life applications, information usually includes spatial, temporal, or spatiotemporal features. Spatiotemporal data has temporal and spatial attributes, and these attributes are often fuzzy. Due to the great significance of fuzzy spatiotemporal data management, how to query fuzzy spatiotemporal data efficiently and effectively has become an important research issue. In that case, this paper formally proposes a new implementation method, which is the query processing of fuzzy spatiotemporal data. In view of the advantages of the most advanced mapping method (R2RML) in data transformation, three algorithms are proposed to transform fuzzy spatiotemporal data from relational database into fuzzy RDF data based on R2RML. On this basis, according to the characteristics of fuzzy RDF data, we give three different fuzzy quantifiers (extreme fuzzy quantifier, range fuzzy quantifier, degree fuzzy quantifier) to represent fuzzy spatiotemporal RDF data. Since SPARQL plays an important role in querying RDF data, it is used for the query of fuzzy spatiotemporal RDF data. In addition, three kinds of fuzzy quantifiers are designed, and the experimental results show the superiority of this method by analyzing experiments in the aspects of the recall and precision.