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Semantic Interoperability Issues and Approaches in the IoT.est Project
 

Semantic Interoperability Issues and Approaches in the IoT.est Project

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P Barnaghi, Semantic Interoperability Issues and Approaches in the IoT.est Project, at the IERC AC4 Semantic interoperability Workshop (during the IoT-week 2012), Venice, Italy, 19 June 2012

P Barnaghi, Semantic Interoperability Issues and Approaches in the IoT.est Project, at the IERC AC4 Semantic interoperability Workshop (during the IoT-week 2012), Venice, Italy, 19 June 2012

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    Semantic Interoperability Issues and Approaches in the IoT.est Project Semantic Interoperability Issues and Approaches in the IoT.est Project Presentation Transcript

    • Semantic Interoperability Issues andApproaches in the IoT.est ProjectPayam BarnaghiCentre for Communication Systems ResearchUniversity of SurreyGuildford, UKIERC AC4 Semantic interoperability Workshop19 June, 2012, Venice, Italy
    • Consortium• 8 partners, 7 countries• Project Lead:CCSR, University of Surrey• Duration:36 monthsIndustry PTIN, ATOS, SIESME TT, AIResearch Centre NICTHigher Education UNIS, UASO
    • IoT.est – a quick snapshot• IoT.est will develop a test-driven service creation environment (SCE)for Internet of Things enabled business services.• The SCE will enable the acquisition of data and control/actuation ofsensors, objects and actuators.• The project will provide the means and tools to define and instantiateIoT services that exploit data across domain boundaries;• IoT.est will facilitate run-time monitoring and will enable autonomousservice adaptation to environment/context and network parameter(e.g. QoS) changes.
    • IoT.est: The Key issues• IoT enabled Business Services: Machine interpretable (semantic)descriptions• Service Composition: A Knowledge based approach• Service Components: Re-usable, interoperable and adaptive• Abstraction: Mapping to heterogeneous platforms and large scaledeployment• Testing (Design Time): Automated generation of tests• Monitoring (Run-Time): Context-aware service adaptation• This requires: machine interpretable description + interoperable domainknowledge + automated discovery and composition, reasoning anddecision making
    • (1a) Semantic and data models in IoT.est• Service model– IoT.est service model, IoT-A service model, OWL-S• Entity and resource models– IoT models, W3C SSN• Test models and Test component descriptions• Common models and knowledge-based to describe thedomain knowledge (e.g. LOD)– Linked Sensor (IoT) data approach
    • (1b) Applications to use and/or need for semanticmodeling practices• Linked data approach– using URI’s as names for things;– using HTTP URI’s to look up those names;– providing useful RDF information related to URI’s– including RDF statements that link to other URI’s• Access and discovery mechanisms and interfaces– Logical reasoning and querying large scale data• Ontology alignment and ontology mapping– Semi-automated and manual alignment– Developing alignment and enhancement tools
    • (1c) Languages (formal/non-formal), Technologies(toolkits, SW tools), protocols enabling semanticinteroperability• RDF/OWL representations– We are also investigating alternative representation andreasoning mechanisms for constrained environments (e.g.Binary RDF, IETF approach)• Ontology design tools– Protégé• Common Interface and access end-points– Standard interface and service models (e.g. OGC SoS,SPARQL end-points, etc).• Ontology mapping and alignment– Ontology engineering phase– Automated tools
    • (1d) Possible contributions/inputs to AC4• Comprehensive semantic models for IoT– Integrated service, entity, resource models– Test models and test components• Alignment tools and reference models• Practical uses-case and methodology to create linkedIoT data.
    • References for semantic interoperability• Suparna De, Payam Barnaghi, Martin Bauer, Stefan Meissner, "Service modelling for the Internetof Things", In Proceedings of the Conference on Computer Science and Information Systems(FedCSIS), pp.949-955, Sept. 2011.• Payam Barnaghi, Mirko Presser, Klaus Moessner, "Publishing Linked Sensor Data", InProceedings of the 3rd International Workshop on Semantic Sensor Networks (SSN), Organisedin conjunction with the International Semantic Web Conference (ISWC) 2010, November 2010.• Michael Compton, Payam Barnaghi, Luis Bermudez, Raul Garcia-Castro, Oscar Corcho, SimonCox, John Graybeal, Manfred Hauswirth, Cory Henson, Arthur Herzog, Vincent Huang, KrzysztofJanowicz, W. David Kelsey, Danh Le Phuoc, Laurent Lefort, Myriam Leggieri, Holger Neuhaus,Andriy Nikolov, Kevin Page, Alexandre Passant, Amit Sheth, Kerry Taylor. "The SSN Ontology ofthe W3C Semantic Sensor Network Incubator Group", Journal of Web Semantics, 2012.• Harshal Patni, Cory Henson, Amit Sheth, Linked Sensor Data, In: Proceedings of 2010International Symposium on Collaborative Technologies and Systems (CTS 2010), Chicago, IL,May 17-21, 2010.• Prateek Jain, Pascal Hitzler, Amit P. Sheth, Kunal Verma, and Peter Z. Yeh, “Ontology alignmentfor linked open data”, In Proceedings of the 9th international semantic web conference on Thesemantic web - Volume Part I (ISWC10), Peter F. Patel-Schneider, Yue Pan, Pascal Hitzler,Peter Mika, and Lei Zhang (Eds.), Vol. Part I. Springer-Verlag, Berlin, Heidelberg, 402-417, 2010.
    • IoT.est project: Internet of Things Environment for ServiceCreation and Testinghttp://ict-iotest.eu/iotest/