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SSG4Env EGU2010
 

SSG4Env EGU2010

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    SSG4Env EGU2010 SSG4Env EGU2010 Presentation Transcript

    • SemsorGrid4Env: Semantic Sensor Grids for Rapid Application Development forEnvironmental ManagementFP7-223913
      EuropeanGeosciencesUnion 2010
      FromSensorsto Interoperable Sensor Networks
      Vienna, 6th May 2010
      Jean-Paul Calbimonte,
      Universidad Politécnica de Madrid
      semsorgrid4env.eu
    • Table of Contents
      • TheConsortium
      • Project Challenges and MainOutcomes
      • Project Plan & milestones
      • Highlights
      • Architecture
      • Data management
      • Registries
      • SemanticIntegration
      • ApplicationTier
      EGU 2010 - Vienna, 6 May 2010
      2
    • TheTeam
      Universidad Politécnica de Madrid, (UPM, Spain)
      University of Manchester (UNIMAN, UK)
      National and KapodistrianUniversity of Athens (NKUA, Greece)
      University of Southampton (SOTON, UK)
      DeimosSpace SLU (DMS, Spain)
      EMU Ltd. (EMU, UK)
      TechIdeas (TI, Spain)
      3
      3
      1
      3
      3
      EGU 2010 - Vienna, 6 May 2010
    • Project Challenges
      Integrated information space
      • Discovery new sensor networks
      • Integrate with existing ones
      • Integrate possibly other data sources (e.g., historical databases)
      Rapid development
      • flexible and user-centric decision support systems
      • Use data from multiple autonomous independently deployed sensor networks and other applications.
      4
      EGU 2010 - Vienna, 6 May 2010
    • Main Outcomes (I)
      System Level (WP1)
      An architecturefor the design and implementation of open large-scale Semantic Sensor Grids.
      A reference SemsorGrid4Env implementation instantiating the architecture
      Component-level (WP2-WP5):
      New techniques and tools for semantic-based data management over the heterogeneous data streams that stem from autonomously deployed sensor networks. (WP2)
      Scalable and fault-tolerant resource discovery mechanisms for sensor registries. (WP3)
      The semantic infrastructure (including ontologies) needed to facilitate the integration of data coming from heterogeneous and distributed sensor networks, legacy databases and applications. (WP4)
      Higher-level application programming interfaces that ease the rapid generation of thin applications (e.g., mashups) of data from sensor networks and historical databases. (WP5)
      Two environmental management applications (WP6-WP7)
      5
      EGU 2010 - Vienna, 6 May 2010
    • Main Outcomes (II)
      Fire Risk Monitoring and Warning in Spain
      (technology-driven)
      Coastal and Estuarine Flood Warning in Southern UK.
      (established early adopter community)
      6
      EGU 2010 - Vienna, 6 May 2010
    • 7
      Why SSG4Env?
      • Flood and firehavesignificantenvironmental and economicimpact in Europe
      • Significantpotentialfromemergingtechnologiestoassistusersby:
      • Improvedmonitoringbydeployed & emerging sensor networks
      • New capabilties in data integrationincludinglive data streams
      • Rapid development of flexible and user-centric decision support systems
      • Semantic Web supportingdiscovery and integration
      • SSG4Env combines expertise and technology in all of theseareastoprovidesolutionswhich are simple, live and dynamic
      EGU 2010 - Vienna, 6 May 2010
    • 8
      WorkpackageStructure and Deliverables
      D1.1: Setup of software development technologies
      D1.2: Deployment of technologicalinfrastructure
      D1.3: SemsorGrid4Env Architecture
      D2.1: Data Requirements, Data Management and Analysis Issues and Query-Based Functionalities
      D3.1: Data models and languages for registries in SemsorGrid4Env
      D3.2: Distributed data structures and algorithms for a Semantic Sensor Grid registry
      D4.1: Design of the SemsorGrid4Env ontology-based data integration model
      D5.1: Specification of high-level application programming interfaces
      D6.1: Requirementsspecification
      D6.2: Deployment of the sensor network
      D7.1: Requirementsspecification
      D7.2: Deployment of the FloodNet sensor network in the Solent
      D8.1: Quality and Risk Contingency Plan
      D8.2: GenderAction Plan
      D9.1: SemsorGrid4Env Website
      D9.2: Plan forDisseminationActivities
      D9.3:SWOT Analysis
      8
      EGU 2010 - Vienna, 6 May 2010
    • Main Project Phases
      9
      EGU 2010 - Vienna, 6 May 2010
    • WP1: SSG4Env General Architecture
      Properties:
      • Any service may directly call any other service.
      • Pre-existing services may be called by any service.
      • Independent development of services.
      • Based on WS-* standards: WS-RF, WS-DAI, WS-N.
      Key features:
      • Data tier services wrap concrete data resources.
      • Semantic middleware adds value to services in application and data tiers.
      10
      EGU 2010 - Vienna, 6 May 2010
    • WP2: Data & Stream Query Processor
      • Principal outcomes:
      • SNEE query processor / SNEEql query language
      • Documented requirements from use cases, to the level of queries and data analyses.
      • Support QoS-aware evaluation within in network query optimizer.
      • Developed out-of-network query compiler and evaluator from to support integration queries.
      SELECT RSTREAM t.id, w.speed, w.dirn
      FROM wind[NOW] w, tree[NOW] t
      WHERE t.smoke > 0
      AND sqrt((t.locx - w.locx)^2 +
      (t.locy - w.locy)^2) <= 40
      EGU 2010 - Vienna, 6 May 2010
      11
    • WP3: Semantic Registry
      • Defined the data model stRDF and the query language stSPARQL, based on the paradigm of constraint databases.
      • Represent thematic and spatial metadata that change over time. Coupled with the RDFS/OWL ontologies of WP4.
      • Developed a formal semantics and algebra for stSPARQL on which we base our implementation.
      • Development of Strabon: a centralized implementation of a subset of stSPARQL.
      EGU 2010 - Vienna, 6 May 2010
      12
    • WP4: Semantic Infrastructure
      • Designed, implemented and deployed a Semantic Integration Service
      • Extend existing ontology-based data integration models to take into account sensor networks streaming data, semantic heterogeneity and quality of service
      • Specified a suite of sensor network ontologies that will be used for describing sensors and related data for the SemSorGrid4Env software architecture
      EGU 2010 - Vienna, 6 May 2010
      13
    • WP2: Semantic Integrator
      Ontology-based data access
      O-O mapping
      S2O mappings
      Client
      Queryreconciliation
      q
      qr
      Query canonisation
      Qc
      SNEEql’ (S1 S2 Sn)
      SPARQLSTR (Og)
      SNEEql (S1 S2 Sn)
      SPARQLSTR (O1 O2On)
      DistributedQueryProcessing
      Data decanonisation
      Data reconciliation
      d
      dr
      Dc
      [tuplel1 l2 l3]
      [tripleO1 O2 On]
      [tripleOg]
      SemanticIntegrator
      EGU 2010 - Vienna, 6 May 2010
      14
    • SSG4Env Application Tier (WP 5, 6 & 7)
      • High level API provides functionality for domain developers (API) and domain users (web apps)
      • Supports applications in WP6 and WP7
      • Resource-centric including Linked Data
      • Embraces and investigates interplay of SOA and ROA
      15
      EGU 2010 - Vienna, 6 May 2010
    • Summary (I): Applicationhighlights
      • Application requirement specifications
      • Sensor deployment in the UK Solent area
      • Early mashup developments for flood warning
      • In order to engage more quickly potential users and other stakeholders.
      16
      EGU 2010 - Vienna, 6 May 2010
    • Summary (II): Technicalhighlights
      • Integration platform (WP1)
      • Architecture, validated with the application use cases (WP1)
      • Selection of outlier detection algorithms (WP2)
      • Out-of-network event stream query processor (WP2)
      • TinyOS2 code generator for the in-network SNEE (WP2)
      • Spatio-temporal extension of SPARQL (stSPARQL) (WP3)
      • Ontology-based streaming data access (WP4)
      • Selection of ontologies to be reused (WP4)
      • API combining RESTful and Linked Open Data approaches (WP5)
      • A proposal for the identification, naming and generation of Linked Stream Data (WP5)
      17
      EGU 2010 - Vienna, 6 May 2010
    • SemsorGrid4Env: Semantic Sensor Grids for Rapid Application Development forEnvironmental ManagementFP7-223913
      EuropeanGeosciencesUnion 2010
      FromSensorsto Interoperable Sensor Networks
      Vienna, 6th May 2010
      Jean-Paul Calbimonte
      EGU 2010 - Vienna, 6 May 2010
    • Why SSG4Env is unique?
      • Domaindevelopers and domainusers can access and integrateheterogeneous data more easily
      • Combination of OGC – Semantic Web – REST technologies/approaches
      • ProposalforLinked Data about sensor data
      • Strongfocusonquery-basedaccessto data
      19
      EGU 2010 - Vienna, 6 May 2010
    • Top Level Requirements
      • Mashups provide rapid development of web interfaces to support custom requirements.
      • Mashups require combined access to:
      • Sensed data from multiple sensors.
      • Stored data from multiple sources.
      • Ontologies for linking independent sources.
      • The aim of the architecture is to deliver appropriate abstraction and integration services for the mashups.
      EGU 2010 - Vienna, 6 May 2010
    • TheConsortiumClassified
      Sevenpartners
      Fouruniversities
      2 SME
      1 largecompany
      Fourmajorsectors
      Education
      IT
      AerospaceEngineering
      Environment
      Technologicalcorecompetencies
      Sensor Networks (UNIMAN, SOTON-ECS, NKUA)
      Semantics (UPM, UNIMAN, SOTON-ECS)
      Grid (UNIMAN, TI, SOTON-ECS, UPM)
      P2P (NKUA)
      Rapid ApplicationDevelopment (SOTON-ECS)
      Use Cases
      Floodwarning (EMU, SOTON-GEODATA)
      Firewarning (DMS)
      21
      EGU 2010 - Vienna, 6 May 2010
    • S2O: Mapping streams to ontologies
      conceptmap-def WindSpeedMeasurement
      uri-as
      concat('ssg4env:WindSpeedMeasurement_',
      windsamples.sensorid,windsamples.ts)
      described-by
      attributemap-defhasSpeed
      operation "constant"
      has-column windsamples.speed
      dbrelationmap-def isProducedBy toConcept Sensor
      joins-via
      condition "equals"
      has-column sensors.sensorid
      has-column windsamples.sensorid
      conceptmap-def Sensor
      uri-as
      concat('ssg4env:Sensor_',sensors.sensorid)
      described-by
      attributemap-def hasName
      operation "constant"
      has-column sensors.sensorname
      S:WindSamples
      • ts
      • speed
      • direction
      • sensorid
      WindSpeedMeasurement
      hasSpeedxsd:float
      Measurement
      isProducedBy
      T:Sensors
      - sensorid
      • sensorname
      Sensor
      hasNamexsd:string
      EGU 2010 - Vienna, 6 May 2010
    • Transforming SPARQLSTR to SNEEql
      Semantic Integrator
      SELECTconcat(‘ssg4env.eu#WindSpeedMeasurement' ,
      windsensor.id, windsensor.ts ) as a1 ,
      concat( ‘ssg4env.eu#Sensor' , sensors.sensorid ) as a2
      FROM sensors, windsensor[ FROM NOW - 10 TO NOW MIN]
      WHERE ( sensors.sensorid = windsensor.id )
      PREFIX fire: http://www.semsorgrid4env.eu#
      PREFIX rdf: http://www.w3.org/1999/02/22-rdf-syntax-ns#
      SELECT ?speed ?name
      FROM STREAM <http://www.ssg4env.eu/Readings.srdf>
      [RANGE 10 MINUTE STEP 1 MINUTE]
      WHERE {
      ?WindSpeed a fire:WindSpeedMeasurement;
      fire:hasSpeed ?speed;
      fire:isProducedBy ?sensor;
      fire:hasTimestamp ?time.
      ?sensor a fire:Sensor;
      fire:hasName ?name.
      }
      Work in progress: removing redundant queries, basic optimisations, more complex scenarios