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DATA INTEGRATION SOLUTION FOR PAPER INDUSTRY Industrial Ontologies Group University of Jyväskylä Motivating scenario ! Customer Site (maintenance support)

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Presentation on theme: "DATA INTEGRATION SOLUTION FOR PAPER INDUSTRY Industrial Ontologies Group University of Jyväskylä Motivating scenario ! Customer Site (maintenance support)"— Presentation transcript:

1 DATA INTEGRATION SOLUTION FOR PAPER INDUSTRY Industrial Ontologies Group University of Jyväskylä Motivating scenario ! Customer Site (maintenance support) The alarm data generated by embedded systems are not stored at the maintenance service provider site although they could be used as training samples in machine learning algorithms for predictive maintenance. The data are not linked with experts’ diagnoses. The experts’ decisions and, hence, experts’ knowledge is neither collected nor linked with the alarm data. The solution CentralHub Site Hub Site Hub Site Hub ! SOAP message Central Hub ! SOAP message VPN Metso site (paper production line) ! SOAP message ! SOAP message ! SOAP message MESSAGE HANDLER Parse XML Transform to RDF Store RDF MESSAGE BROWSER SeRQL Query Store RDF ! SOAP message Query Result Transform to HTML Add annotation (XML) Transform to RDF Generic problem Why Semantic Web? Author info Nikitin S., Terziyan V. and Pyötsiä J., Data Integration Solution For Paper Industry, In proceedings of 4th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2007), May 8-12, 2007, Angers, France. Resource Data Information Resource Common Application Domain Integrated Knowledge Querying Presentation Integrated Annotation Semantic Web can be a solution to those problems and situations that we are yet to define… Ora Lassila Resource Data Information Resource Resource Data Information Resource Industry challenges the IT-sector with new requirements that are dictated by the need to offer essentially new services to customers in order to be competitive in the market. These requirements may become difficult to meet using conventional tools and approaches. When integrating data from different sources the growth in the information volumes we want to store and process leads to an unprecedented level of complexity. We could have implemented it without Semantic Web, but…  We do not have a fixed set of use cases for the data storage, nor is that preferred.  New business scenarios may appear at any time during the operation life cycle that will require an extension of the domain model  We may generate new essential data (by analytic algorithms, experts’ opinions, etc.) for storing, based on already collected data. And this information needs to be integrated. The Semantic Web gives us the means to set up an extensible domain model that is easy to query. Our tool does not offer a tailored solution for a particular problem, but instead provides a unified data storage. Dr. Tech. Jouni Pyötsiä Vice President, ICT Development, Metso Automation, Finland Prof. Dr. (Habil) Tech. Vagan Terziyan Professor in Distributed Systems at the Mathematical Information Technology department, University of Jyväskylä, Finland Head of the Industrial Ontologies Group http://www.cs.jyu.fi/ai/vagan Ms. Sc. Sergiy Nikitin Researcher at the Agora Center and a Ph.D. student at the IT faculty of the University of Jyväskylä, Finland Member of the Industrial Ontologies Group http://people.jyu.fi/~senikitiSiteHub XML Query Transform to SeRQL


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