SemsorGrid4Env: Semantic Sensor Grids for Rapid Application Development forEnvironmental ManagementFP7-223913<br />Europea...
Table of Contents<br /><ul><li>TheConsortium
Project Challenges and MainOutcomes
Project Plan & milestones
Highlights
Architecture
Data management
Registries
SemanticIntegration
ApplicationTier</li></ul>EGU 2010 - Vienna, 6 May  2010<br />2<br />
TheTeam<br />Universidad Politécnica de Madrid, (UPM, Spain)<br />University of Manchester (UNIMAN, UK)<br />National and ...
Project Challenges<br />	Integrated information space <br /><ul><li>Discovery new sensor networks
Integrate with existing ones
Integrate possibly other data sources (e.g., historical databases)</li></ul> 	Rapid development <br /><ul><li>flexible and...
Use data from multiple autonomous independently deployed sensor networks and other applications.</li></ul>4<br />EGU 2010 ...
Main Outcomes (I)<br />System Level (WP1)<br />An architecturefor the design and implementation of open large-scale Semant...
Main Outcomes (II)<br />Fire Risk Monitoring and Warning in Spain <br />(technology-driven)<br />	Coastal and Estuarine Fl...
7<br />Why SSG4Env?<br /><ul><li>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
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SSG4Env EGU2010

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SSG4Env EGU2010

  1. 1. SemsorGrid4Env: Semantic Sensor Grids for Rapid Application Development forEnvironmental ManagementFP7-223913<br />EuropeanGeosciencesUnion 2010<br />FromSensorsto Interoperable Sensor Networks<br />Vienna, 6th May 2010<br />Jean-Paul Calbimonte,<br />Universidad Politécnica de Madrid<br />semsorgrid4env.eu<br />
  2. 2. Table of Contents<br /><ul><li>TheConsortium
  3. 3. Project Challenges and MainOutcomes
  4. 4. Project Plan & milestones
  5. 5. Highlights
  6. 6. Architecture
  7. 7. Data management
  8. 8. Registries
  9. 9. SemanticIntegration
  10. 10. ApplicationTier</li></ul>EGU 2010 - Vienna, 6 May 2010<br />2<br />
  11. 11. TheTeam<br />Universidad Politécnica de Madrid, (UPM, Spain)<br />University of Manchester (UNIMAN, UK)<br />National and KapodistrianUniversity of Athens (NKUA, Greece)<br />University of Southampton (SOTON, UK)<br />DeimosSpace SLU (DMS, Spain)<br />EMU Ltd. (EMU, UK)<br />TechIdeas (TI, Spain)<br />3<br />3<br />1<br />3<br />3<br />EGU 2010 - Vienna, 6 May 2010<br />
  12. 12. Project Challenges<br /> Integrated information space <br /><ul><li>Discovery new sensor networks
  13. 13. Integrate with existing ones
  14. 14. Integrate possibly other data sources (e.g., historical databases)</li></ul> Rapid development <br /><ul><li>flexible and user-centric decision support systems
  15. 15. Use data from multiple autonomous independently deployed sensor networks and other applications.</li></ul>4<br />EGU 2010 - Vienna, 6 May 2010<br />
  16. 16. Main Outcomes (I)<br />System Level (WP1)<br />An architecturefor the design and implementation of open large-scale Semantic Sensor Grids.<br />A reference SemsorGrid4Env implementation instantiating the architecture<br />Component-level (WP2-WP5):<br />New techniques and tools for semantic-based data management over the heterogeneous data streams that stem from autonomously deployed sensor networks. (WP2)<br />Scalable and fault-tolerant resource discovery mechanisms for sensor registries. (WP3)<br />The semantic infrastructure (including ontologies) needed to facilitate the integration of data coming from heterogeneous and distributed sensor networks, legacy databases and applications. (WP4)<br />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)<br />Two environmental management applications (WP6-WP7)<br />5<br />EGU 2010 - Vienna, 6 May 2010<br />
  17. 17. Main Outcomes (II)<br />Fire Risk Monitoring and Warning in Spain <br />(technology-driven)<br /> Coastal and Estuarine Flood Warning in Southern UK.<br />(established early adopter community)<br />6<br />EGU 2010 - Vienna, 6 May 2010<br />
  18. 18. 7<br />Why SSG4Env?<br /><ul><li>Flood and firehavesignificantenvironmental and economicimpact in Europe
  19. 19. Significantpotentialfromemergingtechnologiestoassistusersby:
  20. 20. Improvedmonitoringbydeployed & emerging sensor networks
  21. 21. New capabilties in data integrationincludinglive data streams
  22. 22. Rapid development of flexible and user-centric decision support systems
  23. 23. Semantic Web supportingdiscovery and integration
  24. 24. SSG4Env combines expertise and technology in all of theseareastoprovidesolutionswhich are simple, live and dynamic</li></ul>EGU 2010 - Vienna, 6 May 2010<br />
  25. 25. 8<br />WorkpackageStructure and Deliverables<br />D1.1: Setup of software development technologies<br />D1.2: Deployment of technologicalinfrastructure<br />D1.3: SemsorGrid4Env Architecture<br />D2.1: Data Requirements, Data Management and Analysis Issues and Query-Based Functionalities<br />D3.1: Data models and languages for registries in SemsorGrid4Env<br />D3.2: Distributed data structures and algorithms for a Semantic Sensor Grid registry<br />D4.1: Design of the SemsorGrid4Env ontology-based data integration model<br />D5.1: Specification of high-level application programming interfaces<br />D6.1: Requirementsspecification<br />D6.2: Deployment of the sensor network<br />D7.1: Requirementsspecification<br />D7.2: Deployment of the FloodNet sensor network in the Solent<br />D8.1: Quality and Risk Contingency Plan<br />D8.2: GenderAction Plan<br />D9.1: SemsorGrid4Env Website<br />D9.2: Plan forDisseminationActivities<br />D9.3:SWOT Analysis<br />8<br />EGU 2010 - Vienna, 6 May 2010<br />
  26. 26. Main Project Phases<br />9<br />EGU 2010 - Vienna, 6 May 2010<br />
  27. 27. WP1: SSG4Env General Architecture<br />Properties:<br /><ul><li>Any service may directly call any other service.
  28. 28. Pre-existing services may be called by any service.
  29. 29. Independent development of services.
  30. 30. Based on WS-* standards: WS-RF, WS-DAI, WS-N.</li></ul>Key features:<br /><ul><li>Data tier services wrap concrete data resources.
  31. 31. Semantic middleware adds value to services in application and data tiers.</li></ul>10<br />EGU 2010 - Vienna, 6 May 2010<br />
  32. 32. WP2: Data & Stream Query Processor<br /><ul><li>Principal outcomes:
  33. 33. SNEE query processor / SNEEql query language
  34. 34. Documented requirements from use cases, to the level of queries and data analyses.
  35. 35. Support QoS-aware evaluation within in network query optimizer.
  36. 36. Developed out-of-network query compiler and evaluator from to support integration queries.</li></ul>SELECT RSTREAM t.id, w.speed, w.dirn<br />FROM wind[NOW] w, tree[NOW] t<br />WHERE t.smoke > 0<br />AND sqrt((t.locx - w.locx)^2 + <br /> (t.locy - w.locy)^2) <= 40<br />EGU 2010 - Vienna, 6 May 2010<br />11<br />
  37. 37. WP3: Semantic Registry<br /><ul><li>Defined the data model stRDF and the query language stSPARQL, based on the paradigm of constraint databases.
  38. 38. Represent thematic and spatial metadata that change over time. Coupled with the RDFS/OWL ontologies of WP4.
  39. 39. Developed a formal semantics and algebra for stSPARQL on which we base our implementation.
  40. 40. Development of Strabon: a centralized implementation of a subset of stSPARQL.</li></ul>EGU 2010 - Vienna, 6 May 2010<br />12<br />
  41. 41. WP4: Semantic Infrastructure<br /><ul><li>Designed, implemented and deployed a Semantic Integration Service
  42. 42. Extend existing ontology-based data integration models to take into account sensor networks streaming data, semantic heterogeneity and quality of service
  43. 43. Specified a suite of sensor network ontologies that will be used for describing sensors and related data for the SemSorGrid4Env software architecture </li></ul>EGU 2010 - Vienna, 6 May 2010<br />13<br />
  44. 44. WP2: Semantic Integrator<br />Ontology-based data access<br />O-O mapping<br />S2O mappings<br />Client<br />Queryreconciliation<br />q<br />qr<br />Query canonisation<br />Qc<br />SNEEql’ (S1 S2 Sn) <br />SPARQLSTR (Og) <br />SNEEql (S1 S2 Sn) <br />SPARQLSTR (O1 O2On) <br />DistributedQueryProcessing<br />Data decanonisation<br />Data reconciliation<br />d<br />dr<br />Dc<br />[tuplel1 l2 l3]<br />[tripleO1 O2 On]<br />[tripleOg]<br />SemanticIntegrator<br />EGU 2010 - Vienna, 6 May 2010<br />14<br />
  45. 45. SSG4Env Application Tier (WP 5, 6 & 7)<br /><ul><li>High level API provides functionality for domain developers (API) and domain users (web apps)
  46. 46. Supports applications in WP6 and WP7
  47. 47. Resource-centric including Linked Data
  48. 48. Embraces and investigates interplay of SOA and ROA</li></ul>15<br />EGU 2010 - Vienna, 6 May 2010<br />
  49. 49. Summary (I): Applicationhighlights<br /><ul><li>Application requirement specifications
  50. 50. Sensor deployment in the UK Solent area
  51. 51. Early mashup developments for flood warning
  52. 52. In order to engage more quickly potential users and other stakeholders.</li></ul>16<br />EGU 2010 - Vienna, 6 May 2010<br />
  53. 53. Summary (II): Technicalhighlights<br /><ul><li>Integration platform (WP1)
  54. 54. Architecture, validated with the application use cases (WP1)
  55. 55. Selection of outlier detection algorithms (WP2)
  56. 56. Out-of-network event stream query processor (WP2)
  57. 57. TinyOS2 code generator for the in-network SNEE (WP2)
  58. 58. Spatio-temporal extension of SPARQL (stSPARQL) (WP3)
  59. 59. Ontology-based streaming data access (WP4)
  60. 60. Selection of ontologies to be reused (WP4)
  61. 61. API combining RESTful and Linked Open Data approaches (WP5)
  62. 62. A proposal for the identification, naming and generation of Linked Stream Data (WP5)</li></ul>17<br />EGU 2010 - Vienna, 6 May 2010<br />
  63. 63. SemsorGrid4Env: Semantic Sensor Grids for Rapid Application Development forEnvironmental ManagementFP7-223913<br />EuropeanGeosciencesUnion 2010<br />FromSensorsto Interoperable Sensor Networks<br />Vienna, 6th May 2010<br />Jean-Paul Calbimonte<br />EGU 2010 - Vienna, 6 May 2010<br />
  64. 64. Why SSG4Env is unique?<br /><ul><li>Domaindevelopers and domainusers can access and integrateheterogeneous data more easily
  65. 65. Combination of OGC – Semantic Web – REST technologies/approaches
  66. 66. ProposalforLinked Data about sensor data
  67. 67. Strongfocusonquery-basedaccessto data</li></ul>19<br />EGU 2010 - Vienna, 6 May 2010<br />
  68. 68. Top Level Requirements<br /><ul><li>Mashups provide rapid development of web interfaces to support custom requirements.
  69. 69. Mashups require combined access to:
  70. 70. Sensed data from multiple sensors.
  71. 71. Stored data from multiple sources.
  72. 72. Ontologies for linking independent sources.
  73. 73. The aim of the architecture is to deliver appropriate abstraction and integration services for the mashups. </li></ul>EGU 2010 - Vienna, 6 May 2010<br />
  74. 74. TheConsortiumClassified<br />Sevenpartners<br />Fouruniversities<br />2 SME<br />1 largecompany<br />Fourmajorsectors<br />Education<br />IT<br />AerospaceEngineering<br />Environment<br />Technologicalcorecompetencies<br />Sensor Networks (UNIMAN, SOTON-ECS, NKUA)<br />Semantics (UPM, UNIMAN, SOTON-ECS)<br />Grid (UNIMAN, TI, SOTON-ECS, UPM)<br />P2P (NKUA)<br />Rapid ApplicationDevelopment (SOTON-ECS)<br />Use Cases<br />Floodwarning (EMU, SOTON-GEODATA)<br />Firewarning (DMS)<br />21<br />EGU 2010 - Vienna, 6 May 2010<br />
  75. 75. S2O: Mapping streams to ontologies<br />conceptmap-def WindSpeedMeasurement <br /> uri-as <br /> concat('ssg4env:WindSpeedMeasurement_',<br />windsamples.sensorid,windsamples.ts) <br /> described-by<br />attributemap-defhasSpeed <br /> operation "constant" <br /> has-column windsamples.speed<br />dbrelationmap-def isProducedBy toConcept Sensor <br /> joins-via <br /> condition "equals" <br /> has-column sensors.sensorid <br /> has-column windsamples.sensorid<br />conceptmap-def Sensor<br /> uri-as<br /> concat('ssg4env:Sensor_',sensors.sensorid)<br /> described-by<br />attributemap-def hasName<br /> operation "constant" <br /> has-column sensors.sensorname<br />S:WindSamples<br /><ul><li>ts
  76. 76. speed
  77. 77. direction
  78. 78. sensorid</li></ul>WindSpeedMeasurement<br />hasSpeedxsd:float<br />Measurement<br />isProducedBy<br />T:Sensors<br />- sensorid<br /><ul><li>sensorname</li></ul>Sensor<br />hasNamexsd:string<br />EGU 2010 - Vienna, 6 May 2010<br />
  79. 79. Transforming SPARQLSTR to SNEEql<br />Semantic Integrator<br />SELECTconcat(‘ssg4env.eu#WindSpeedMeasurement' , <br /> windsensor.id, windsensor.ts ) as a1 , <br />concat( ‘ssg4env.eu#Sensor' , sensors.sensorid ) as a2 <br />FROM sensors, windsensor[ FROM NOW - 10 TO NOW MIN] <br />WHERE ( sensors.sensorid = windsensor.id )<br />PREFIX fire: http://www.semsorgrid4env.eu#<br />PREFIX rdf: http://www.w3.org/1999/02/22-rdf-syntax-ns#<br />SELECT ?speed ?name <br />FROM STREAM <http://www.ssg4env.eu/Readings.srdf> <br /> [RANGE 10 MINUTE STEP 1 MINUTE] <br />WHERE { <br /> ?WindSpeed a fire:WindSpeedMeasurement; <br />fire:hasSpeed ?speed; <br />fire:isProducedBy ?sensor; <br />fire:hasTimestamp ?time.<br /> ?sensor a fire:Sensor; <br />fire:hasName ?name. <br />}<br />Work in progress: removing redundant queries, basic optimisations, more complex scenarios<br />

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