Stream reasoning and complex event processing in ETALIS

  • Authors:

  • Darko Anicic;Sebastian Rudolph;Paul Fodor;Nenad Stojanovic

  • Affiliations:

  • FZI Research Center for Information Technology, Karlsruhe, Germany. E-mail: nenad.stojanovic@fzi.de;Karlsruhe Institute of Technology, Karlsruhe, Germany. E-mail: rudolph@kit.edu;Stony Brook University, New York, NY, USA. E-mail: pfodor@cs.stonybrook.edu;FZI Research Center for Information Technology, Karlsruhe, Germany. E-mail: nenad.stojanovic@fzi.de

  • Venue:
  • Semantic Web - On linked spatiotemporal data and geo-ontologies
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

Addressing dynamics and notifications in the Semantic Web realm has recently become an important area of research. Run time data is continuously generated by multiple social networks, sensor networks, various on-line services and so forth. How to get advantage of this continuously arriving data events remains a challenge --that is, how to integrate heterogeneous event streams, combine them with background knowledge e.g., an ontology, and perform event processing and stream reasoning. In this paper we describe ETALIS --a system which enables specification and monitoring of changes in near real time. Changes can be specified as complex event patterns, and ETALIS can detect them in real time. Moreover the system can perform reasoning over streaming events with respect to background knowledge. ETALIS implements two languages for specification of event patterns: ETALIS Language for Events, and Event Processing SPARQL. ETALIS has various applicabilities in capturing changes in semantic networks, broadcasting notifications to interested parties, and creating further changes based on processing of the temporal, static, or slowly evolving knowledge.