Tutorial ESWC2011 Building Semantic Sensor Web - 01 - Introduction
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Tutorial ESWC2011 Building Semantic Sensor Web - 01 - Introduction

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ESWC 2011 Tutorial Seman

ESWC 2011 Tutorial Seman

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    Tutorial ESWC2011 Building Semantic Sensor Web - 01 - Introduction Tutorial ESWC2011 Building Semantic Sensor Web - 01 - Introduction Presentation Transcript

    • BuildingSemantic Sensor Webs and Applications
      ESWC 2011 Tutorial
      29 May 2011
    • Tutorial Objectives
      • Knowledgeof thebasicconcepts and toolstobuildsemantically-enabledapplications and servicesthatrelypartiallyortotallyondata comingfrom sensor networks
      • Whom of thisgroup are you in?
      • Developerswhowishtobuildsuchapplications
      • Peopleinterested in thebasicconcepts of semantic sensor web applications
      • Experts in Semantic Sensor Web applications
    • Whomwe are?
      • Oscar Corcho (UPM)
      • Alasdair Gray (UNIMAN)
      • KostisKyzirakos (NKUA)
      • Jean Paul Calbimonte (UPM)
      • Kevin Page (SOTON)
    • Schedule fortoday
      • Introduction (20’)
      • Semantic Sensor Web components (20’)
      • DiscoveringSourcesfor a Region: (20 minutes theory + 30 minutes practical)
      • Coffeebreak (20 minutes)
      • QueryingStreaming Data throughOntologies: (20 minutes theory + 30 minutes practical)
      • Sensor Data and SemanticMashups: (20 minutes theory + 30 minutes practical)
    • IntroductiontotheSemantic Sensor Web
      ESWC 2011 Tutorial
      29 May 2011
    • Sensor Networks
      • Increasingavailability of cheap, robust, deployablesensors as ubiquitousinformationsources
      • Dynamic and reactive, butnoisy, and unstructured data streams
      Source: Antonis Deligiannakis
    • The Sensor Web
      • Sensor networksmaybenetworked, mostlywireless, hence global and integrated
      • Universal, web-based access to sensor data
      • Each network with some kind of authority and administration
      • Sensor networks vs robust networks
      6
      Source: Adaptedfrom Alan Smeaton’sinvitedtalk at ESWC2009
    • Sensor Web: Isthispart of the Web/Internet?
      7
      Source: SemsorGrid4Env consortium
    • Who are theendusers of sensor networks?
      Theclimatechangeexpert, or a simple citizen
      Source: Dave de Roure
    • Most of you are computer scientists. Why is it worth working on this?
      • You may like helping scientists, or…
      • You want to address any of the following challenges in Computer Science:
      Scale, scalable
      Autonomic behaviour versus control
      Persistent, heterogeneous, evolving
      Deployment challenge
      Some mobile devices
      Source: Dave de Roure
    • A set of challenges in sensor data management
      • Data Provisioning
      Complexity of acquisition: distributed sources, data volumes, uncertainty, data quality, incompleteness
      Pre-processing incoming data: calibration on instruments (specific), lack of re-grid, calibration, gap-filling features
      Tools for data ingestion needed: generic, customizable, provide estimates, uncertainty degree, etc.
      • Spatial/temporal
      • Analysis, modeling
      Discovery: identify sources, metadata
      Data quality: gaps, faulty data, loss, estimates
      Analysis models
      Republish analytic results, computations, 
      Workflows for data stream processing
      10
      Source: Data Management in theWorldWide Sensor Web. Balazinska et al. IEEE Pervasive Computing, 2007
    • A set of challenges in sensor data management
      • Interoperability
      Data aggregation/integration
      • Uncertainty, data quality
      Noise, failures, measurement errors, confidence, trust
      • Distributed processing
      High volume, time critical
      Fault-tolerance
      Load management 
      Stream processing features
      Continuous queries
      Live & historical data
      11
      Source: Data Management in the WorldWide Sensor Web. Balazinska et al. IEEE Pervasive Computing, 2007
    • A semanticperspectiveonthesechallenges
      • Sensor data querying and (pre-)processing
      Data heterogeneity Data integration and fusion
      Data quality
      New inferencecapabilitiesrequiredtodealwith sensor information
      • Sensor data modelrepresentation and management
      For data publication, integration and discovery
      Bridgingbetween sensor data and ontologicalrepresentationsfor data integration Abstractionlevel
      Eventmodels
      • Rapid development of applications
      • Userinteractionwith sensor data
      Source: FiveChallengesfortheSemantic Sensor Web. García-Castro R, Corcho O.Semantic Web Journal, 2010
    • Challenges. A high-levelapplication
      Mashupdevelopment
      Registry
      InformationIntegration
      Sensor Network Ontologies