Paper 109 (In-Use track)

RDF-Gen: Generating RDF from streaming and archival data

Author(s): Georgios Santipantakis, Christos Doulkeridis, Konstantinos Kotis, George Vouros

Abstract: Recent state-of-the-art approaches and technologies for generating RDF graphs from non-RDF data use languages that have been designed for specifying trans-formations or mappings to data of various kind of format. This paper presents a new approach for the generation of ontology-annotated RDF graphs, linking data from multiple heterogeneous streaming and archival data sources, with high throughput and low latency. To support this, and in contrast to existing approaches, we propose embedding in the RDF generation process a close-to-sources data processing and linkage stage, supporting the fast template-driven generation of triples in a subsequent stage. This approach, called RDF-Gen has been implemented as a SPARQL-based RDF generation approach. RDF-Gen is evaluated against the latest related work of RML and SPARQL-Generate, using real world datasets.

Keywords: RDF generation; RDF knowledge graph; data-to-RDF mapping

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