Affiliation:
1. Department of Computer Science, South East European University, Ilindenska n. 335, Tetovë 1200, Macedonia
2. Department of Computer Engineering, University of Prishtina, Kodra e diellit pn, Prishtinë 10000, Kosova
Abstract
The synergy of Data Stream Management Systems and Semantic Web applications has steered towards a new paradigm known as Stream Reasoning. The Semantic Web standards for knowledge base modeling and querying, namely RDF, OWL and SPARQL, has extensively been used by the Stream Reasoning community. However, the Semantic Web rule languages, such as SWRL and RIF, have never been used in stream data applications. Instead, different non-Semantic Web rule systems have been approached. Since RIF is primarily intended for exchanging rules among systems, we focused on SWRL applications with stream data. This proves difficult following the SWRL’s open world semantics. To overcome SWRL’s expressivity issues we propose an infrastructure extension, which will enable SWRL reasoning with stream data. Namely, a query processing system, such as C-SPARQL, was layered under SWRL to support closed-world and time-aware reasoning. Moreover, OWLAPI constructs were utilized to enable non-monotonicity, while SPARQL constructs were used to enable negation as failure. Water quality monitoring was used as a validation domain of the proposed system.
Publisher
World Scientific Pub Co Pte Lt
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Linguistics and Language,Information Systems,Software
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Integration of Semantics Into Sensor Data for the IoT;International Journal on Semantic Web and Information Systems;2020-10