Generating linked RDF data from heterogeneous streaming and archival data sources: Populating the datAcron ontology

Analysis of moving objects behaviour requires surveillance data (i.e. spatio-temporal data concerning objects’ positional information), together with information about moving objects, occurring events and their context. Thus, data from disparate sources must be converted to a common format, integrated w.r.t. a specific model. This paper proposes a generic framework for generating RDF from heterogenous data formats - exploiting the specification of graph templates. We present and demonstrate the benefits of the proposed RDF generation process for the provision of semantically annotated data revolving around the notion of objects’ trajectory. The process is demonstrated for the population of the datAcron ontology using real-world domain-specific data sources.