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Ontology-Based Introspection in Support of Stream Reasoning
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, Faculty of Science & Engineering. (KPLAB - Knowledge Processing Lab)
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, Faculty of Science & Engineering. (KPLAB - Knowledge Processing Lab)
2015 (English)In: Proceedings of the Joint Ontology Workshops (JOWO 2015), Buenos Aires, Argentina, July 25-27, 2015: The Joint Ontology Workshops - Episode 1 / [ed] Odile Papini, Salem Benferhat, Laurent Garcia, Marie-Laure Mugnier, Eduardo Fermé, Thomas Meyer, Renata Wassermann, Torsten Hahmann, Ken Baclawski, Adila Krisnadhi, Pavel Klinov, Stefano Borgo and Oliver Kutz Daniele Porello15, Rheinisch-Westfaelische Technische Hochschule Aachen * Lehrstuhl Informatik V , 2015, Vol. 1517, 1-8 p.Conference paper, Published paper (Other academic)
Abstract [en]

Building complex systems such as autonomous robots usually require the integration of a wide variety of components including high-level reasoning functionalities. One important challenge is integrating the information in a system by setting up the data flow between the components. This paper extends our earlier work on semantic matching with support for adaptive on-demand semantic information integration based on ontology-based introspection.  We take two important stand-points.  First, we consider streams of information, to handle the fact that information often becomes continually and incrementally available.  Second, we explicitly represent the semantics of the components and the information that can be provided by them in an ontology.  Based on the ontology our custom-made stream configuration planner automatically sets up the stream processing needed to generate the streams of information requested. Furthermore, subscribers are notified when properties of a stream changes, which allows them to adapt accordingly. Since the ontology represents both the system's information about the world and its internal stream processing many other powerful forms of introspection are also made possible. The proposed semantic matching functionality is part of the DyKnow stream reasoning framework and has been integrated in the Robot Operating System (ROS).

Place, publisher, year, edition, pages
Rheinisch-Westfaelische Technische Hochschule Aachen * Lehrstuhl Informatik V , 2015. Vol. 1517, 1-8 p.
Series
CEUR Workshop Proceedings, ISSN 1613-0073
Keyword [en]
ontology, introspection, semantic matching, stream reasoning, stream processing, stream, configuration, integration
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-120303OAI: oai:DiVA.org:liu-120303DiVA: diva2:843157
Conference
1st Joint Ontology Workshops (JOWO-2015), Buenos Aires, Argentina, July 25-27, 2015
Projects
CUGSCENIITCADICSELLIITCUAS
Note

Workshops held at the 24th International Joint Conference on Artificial Intelligence - IJCAI 2015, Buenos Aires, Argentina, July 25-27, 2015

Available from: 2015-07-27 Created: 2015-07-27 Last updated: 2016-07-05Bibliographically approved

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de Leng, DanielHeintz, Fredrik

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CiteExportLink to record
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