Dietze, Stefan; Benn, Neil; Yu, Hong Qing; Pedrinaci, Carlos; Makni, Bassem; Liu, Dong; Lambert, Dave and Domingue, John
(2010).
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Abstract
Semantics are used to mark up a wide variety of data-centric Web resources but, are not used in significant numbers to annotate online services — that is despite considerable research dedicated to Semantic Web Services (SWS). This is partially due to the complexity of comprehensive SWS models aiming at automation of service-oriented tasks such as discovery, composition, and execution. This has led to the emergence of a new approach dubbed Linked Services which is based on simplified service models that are easier to populate and interpret and accessible even to non-experts. However, such Minimal Service Models so far do not cover all execution-related aspects of service automation and merely aim at enabling more comprehensive service search and clustering. Thus, in this paper, we describe our approach of combining the strengths of both distinct approaches to modeling Semantic Web Services – “lightweight” Linked Services and “heavyweight” SWS automation – into a coherent SWS framework. In addition, an implementation of our approach based on existing SWS tools together with a proof-of-concept prototype used within the EU project NoTube is presented.
| Item Type: | Conference or Workshop Item |
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| Copyright Holders: | 2010 The Authors |
| Extra Information: | Proceedings of the 4th International Workshop on Service Matchmaking and Resource Retrieval in the Semantic Web
Held at The 9th International Semantic Web Conference (ISWC 2010), Shanghai, China, 7-11 Nov 2010 Shanghai, China, November 8, 2010. Edited by Abraham Bernstein, Paul Grace, Matthias Klusch, Massimo Paolucci |
| Keywords: | Semantic Web Services; Linked Services; linked data; IPTV |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) |
| Related URLs: | |
| Item ID: | 24707 |
| Depositing User: | Kay Dave |
| Date Deposited: | 24 Nov 2010 10:47 |
| Last Modified: | 25 Jul 2017 10:41 |
| URI: | http://oro.open.ac.uk/id/eprint/24707 |
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