Tech Reports
Tech Report kmi-09-06 Abstract
On the Integration of Services with the Web of Data
Techreport ID: kmi-09-06
Date: 2009
Author(s): Carlos Pedrinaci,John Domingue,Reto Krummenacher
Research on Semantic Web Services has pursued the automation of tasks on the Web by enriching Web services technologies with semantics. Thus far, however, Semantic Web Services have failed to gain a significant uptake due to a big extent to the complexity of the solutions proposed and the limited amount of high quality data and ontologies that were available until recently. In this report we explore the relationship between Semantic Web Services and the Web of Data. We identify the potential benefits that could be obtained by adequately integrating these so far disconnected worlds. We present a vision outlining how this integration could take place by using simpler vocabularies for describing services, through the adoption of linked data principles for publishing services on the Web, and by reusing principles originating research on Knowledge Based Systems and Knowledge Engineering such as the Blackboard model and Problem-Solving Methods. The vision presented herein represents at the same time the outline of a research roadmap we are pursuing and we shall, where appropriate, illustrate some of these ideas through concrete examples and prototypes we have already developed.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Multimedia and Information Systems is...

We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
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