Author(s): Ruben Taelman, Riccardo Tommasini, Joachim Van Herwegen, Ruben Verborgh, Emanuele Della Valle, Erik Mannens
Abstract: RDF Stream Processing(RSP) is a rapidly evolving area of research that focuses on extensions of the Semantic Web in order to model and process Web data streams. While state-of-the-art approaches concentrate on server-side processing of RDF streams, we investigate the TPF-QS method for server-side publishing of RDF streams, which moves the workload of continuous querying to clients. We formalize TPF-QS in terms of the RSP-QL reference model in order to formally compare it with existing RSP query languages. We experimentally validate that, compared to the state of the art, the server load of TPF-QS scales better with increasing numbers of concurrent clients in case of simple queries, at the cost of increased bandwidth consumption. This shows that TPF-QS is an important first step towards a viable solution for Web-scale publication and continuous processing of RDF streams.
Keywords: Linked Data; RDF stream processing; continuous querying; TPF-QS; RSP-QL; SPARQL