Abstract
SPARQL was originally developed to process queries over finite-length datasets encoded as RDF graphs. Processing of infinite data streams can be enabled through continuous incremental evaluation of an incoming event stream. SPARQL Update provides tools for interconnecting queries, enabling event processing applications to be constructed out of multiple incrementally processed collaborating rules. These rule networks can perform event processing on heterogeneous event structures. Heterogeneous event support combined with the capability to synthesise new events enables the creation of layered event processing networks. In this paper, we review the different types of complex event processing building blocks presented in the literature and show their translations to SPARQL Update rules through examples, supporting a modular and layered approach. The interconnected examples demonstrate the creation of an elaborate network for solving event processing tasks. The performance of the example event processing network is verified on the INSTANS platform.
| Original language | English |
|---|---|
| Pages (from-to) | 57-69 |
| Number of pages | 13 |
| Journal | Journal on Data Semantics |
| Volume | 6 |
| Issue number | 2 |
| Early online date | 23 Sept 2016 |
| DOIs | |
| Publication status | Published - Jun 2017 |
| MoE publication type | A1 Journal article-refereed |
Keywords
- Complex event processing
- SPARQL
- heterogeneous events
- Stream processing
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