Litcius/Paper detail

A comprehensive overview of RDF for spatial and spatiotemporal data management

Fu Zhang, Qingzhe Lü, Zhenjun Du, Xu Chen, Chunhong Cao

2021The Knowledge Engineering Review11 citationsDOI

Abstract

Abstract Currently, a large amount of spatial and spatiotemporal RDF data has been shared and exchanged on the Internet and various applications. Resource Description Framework (RDF) is widely accepted for representing and processing data in different (including spatiotemporal) application domains. The effective management of spatial and spatiotemporal RDF data are becoming more and more important. A lot of work has been done to study how to represent, query, store, and manage spatial and spatiotemporal RDF data. In order to grasp and learn the main ideas and research results of spatial and spatiotemporal RDF data, in this paper, we provide a comprehensive overview of RDF for spatial and spatiotemporal data management. We summarize spatial and spatiotemporal RDF data management from several essential aspects such as representation, querying, storage, performance assessment, datasets, and management tools. In addition, the direction of future research and some comparisons and analysis are also discussed in depth.

Topics & Concepts

RDFComputer scienceSimple Knowledge Organization SystemRDF SchemaSpatial analysisSPARQLData managementCwmInformation retrievalData miningData scienceGeographySemantic WebRemote sensingData Management and AlgorithmsSemantic Web and OntologiesAdvanced Database Systems and Queries