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dc.contributor.authorChen-Burger, Y-H
dc.contributor.authorLin, F-P
dc.date.accessioned2008-05-09T09:45:15Z
dc.date.available2008-05-09T09:45:15Z
dc.date.issued2005-05
dc.identifier.citationChen-Burger, Y-H. and Lin, F-P. (2005) A Semantic-based Workflow Choreography for Integrated Sensing and Processing, Proceedings of the 9th IEEE International Workshop on Cellular Neural Networks and their Applications, Hsin-chu, Taiwan, May 28-30, 2005.en
dc.identifier.issn978-0-7803-9185-7
dc.identifier.urihttp://www.aiai.ed.ac.uk/project/ix/documents/2005/2005-cnna-chenburger-ecogrid.pdf
dc.identifier.urihttp://hdl.handle.net/1842/2180
dc.descriptionThe University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the authorâ s and shouldnâ t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.en
dc.description.abstractReal-time automatic and continuous information gathering through EcoGrid offers an unique and immense opportunity for long term ecological monitoring and planning. However, the vast amount of raw data gathered must be dealt with efficiently and effectively so that they may be timely turned into useable information to assist ecological management. In addition, Ecological data tends to subject to environmental changes and exception-prone so that their qualities vary. Adaptive business process modelling (BPM) techniques provide rich conceptualisation to support workflow systems to perform integrated analytical and documentation tasks flexibly and efficiently. We present one such BPM and show how adaptive workflow systems, like those developed at AIAI, can take advantage of Enterprise Models represented in FBPML to provide effective support to users in real Grid environments.en
dc.contributor.sponsorEngineering and Physical Sciences Research Council (EPSRC)en
dc.format.extent164776 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherIEEE Computer Societyen
dc.subjectInformaticsen
dc.subjectartificial intelligenceen
dc.subjectComputer Scienceen
dc.subjectbusiness process modellingen
dc.subjectArtificial Intelligence Applications Institute
dc.titleA Semantic-based Workflow Choreography for Integrated Sensing and Processingen
dc.typeConference Paperen


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