Manfred Linking the Real World

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Manfred Linking the Real World

  1. 1. Digital Enterprise Research Institute www.deri.ie Linking the Real World Manfred Hauswirth Copyright 2011 Digital Enterprise Research Institute. All rights reserved. Enabling networked knowledge
  2. 2. Digital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  3. 3. DERI’s MissionDigital Enterprise Research Institute www.deri.ie Enabling & exploiting Networked Knowledge Enabling networked knowledge
  4. 4. About DERIDigital Enterprise Research Institute www.deri.ie  Founded June 2003 as a CSET (Centre for Science, Engineering and Technology).  Link scientists and engineers / academia and industry  Fundamental research  Development of Irish-based technology companies  Attract industry  Education & outreach  DERI Institute  CSET  Commercialization, DAI  EU, EI, direct industry, IRCSET  DERI strategic plan responds to priorities  Local: University focus on Informatics, Physical & Computational Sciences  National: SMART Economy, Program for Government  International: EU Digital Agenda Enabling networked knowledge
  5. 5. About DERIDigital Enterprise Research Institute www.deri.ie  Number one in our core space  Research Publications > 1000  Participation in 17 standardisation groups (W3C, OASIS)  Approx. 140 members from 30 nations  57 PhDs /Masters  42 completed PhDs/Masters  Core Industrial Partners:  MNC’s: Cisco, Avaya, Bel-Labs, Ericsson…  SME’s: Storm, Celtrak, OpenLink……  Research: FBK  Total Research Grants: > €60 million  SFI, EU Framework, Enterprise Ireland, Industry  Currently 18 EU project running  Industry funded projects with Fujitsu Labs Japan, Cisco, Google, Renault, EADS, Fidelity,… Enabling networked knowledge
  6. 6. Key Industry CollaborationsDigital Enterprise Research Institute www.deri.ie CSET Partners Enabling networked knowledge6
  7. 7. DERI Innovation ApproachDigital Enterprise Research Institute www.deri.ie • Seevl • Sindice.com Spin Outs • Peracton • Atom • PEPPR • IVEA Commerci- alisation • Joint projects • Patents and Industry Licensing • DERI Applied Research Collaboration Innovation Excellence• W3C• OASIS• SIOC• VOID, DCAT• schema.org• OData Standards • Drupal 7 Open • Semantic Desktop • SIREn Source Prototypes Enabling networked knowledge
  8. 8. The DERI HouseDigital Enterprise Research Institute www.deri.ie DERI Applied Research Commercialisation eBusiness Green & eLearning Financial Services Sustainable IT Health Care Cyber Data eGovernment Life Sciences Security Linked Cloud Analy Data tics Information Security, Cloud Data Sensor Social Software Mining Privacy Management Middleware and Retrieval & Trust Data Natural Service Reasoning and Knowledge Visualisation Language Oriented Querying Discovery and Interaction Processing Architecture DERI is designed to provide an integrated solution Enabling networked knowledge
  9. 9. Solve which problem?Digital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  10. 10. A Network of KnowledgeDigital Enterprise Research Institute www.deri.ie  Interconnected  Universal  All encompassing  Assists humans, organizations and systems in problem solving  Enable global and local collaboration Enabling networked knowledge
  11. 11. A Network of KnowledgeDigital Enterprise Research Institute www.deri.ie  Interconnected  Universal All encompassing •Application • Search Research Domains • Collaboration • Commercialization • Information Mining • MiddlewareLinked Data  assists humans, organizations and systems with problem solving  enabling innovation and increased productivity Enabling networked knowledge
  12. 12. Two Key IngredientsDigital Enterprise Research Institute www.deri.ie 1. RDF – Resource Description Framework Graph based Data – nodes and arcs  Identifies objects (URIs)  Interlink information (Relationships) 2. Vocabularies (Ontologies)  provide shared understanding of a domain  organise knowledge in a machine-comprehensible way  give an exploitable meaning to the data Enabling networked knowledge 12 of 46
  13. 13. Why Graphs and Ontologies?Digital Enterprise Research Institute www.deri.ie Cities:Dublin Geo:hasLargestCity 84421km2 Wikipedia.org Geo:IslandOfIreland Geo:hasCapital Geo:area Geo:locatedOn EU:RepublicOfIreland EU:RepublicOfIreland Gov:hasDepartment Gov:hasTaoiseach Gov.ie Person:EndaKenny IE:DepartmentOfFinance Enabling networked knowledge
  14. 14. Linked Open Data CloudDigital Enterprise Research Institute www.deri.ie 2008 2007 2008 2010 2009 2008 2009 2008 Enabling networked knowledge 14 14
  15. 15. Linked Data DomainsDigital Enterprise Research Institute www.deri.ie BestBuyhttp://lod-cloud.net/ Overstock.com Facebook Powered US government UK government by DERI! Media User-generated Government Publications BBC New York Times Cross-domain Geo Life sciences LinkedGeoData Over 200 open data sets with more than 25 billion facts, interlinked by 400 million typed links, doubling every 10 month! Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. Enabling networked knowledge 15
  16. 16. Challenges of Big DataDigital Enterprise Research Institute www.deri.ie “90% of the data in the world today has been created in the last two years alone” – IBM The bringing together of a vast amount of data from public and private sources […] is what Big Data is all about,” – IDC Enabling networked knowledge
  17. 17. How to exploit Big Data?Digital Enterprise Research Institute www.deri.ie Solutions required for  Management and Integration  Abstraction and Reasoning  Analytics and Visualization  Interaction and Collaboration  Domain Knowledge and  Integration into a coherent Framework! Enabling networked knowledge
  18. 18. Knowledge DashboardDigital Enterprise Research Institute www.deri.ie Analytics Visualisation Abstraction Reasoning Networked Data Enabling networked knowledge
  19. 19. What is a Smart City?Digital Enterprise Research Institute www.deri.ie  Invests in  human and social capital  traditional/modern infrastructure  that  fuels sustainable economic development  and high quality of life  while  managing natural resources  through  participatory governance Enabling networked knowledgehttp://ideas.repec.org/p/dgr/vuarem/2009-48.html
  20. 20. Digital Enterprise Research Institute www.deri.ieA Smart City removes silos movingtowards a connected digital layer. Enabling networked knowledge
  21. 21. Silos’ Value Untapped ValueDigital Enterprise Research Institute www.deri.ie Enabling networked knowledgehttp://www.mckinsey.com/mgi/publications/ig_data/pdfs/MGI_big_data_full_report.pdf
  22. 22. Digital Enterprise Research Institute www.deri.ieA Smart City driver of change will be Data. Enabling networked knowledge
  23. 23. Digital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  24. 24. The ProblemDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  25. 25. GoalDigital Enterprise Research Institute www.deri.ie Streams are just yet another form/source of linked data  Semantic description of sensors, streams, events, observations, etc.  “Senso ergo sum” – semantic descriptions down to the sensor level  Web protocols down to the sensor level  SPARQL-like access to streams and sensors  Infrastructure framework Enabling networked knowledge
  26. 26. Keep it simple, Stupid!Digital Enterprise Research Institute www.deri.ie Application := Data + Services Application LOD REST Enabling networked knowledge
  27. 27. KISS revisitedDigital Enterprise Research Institute www.deri.ie Application CQELS REST SPARQL Linked Streams Linked Data Virtual COAP Sensors Sensors Enabling networked knowledge
  28. 28. Digital Enterprise Research Institute www.deri.ie Where are we right now? Enabling networked knowledge
  29. 29. Digital Enterprise Research Institute www.deri.ie Sensors, streams, events, observations Enabling networked knowledge
  30. 30. W3C SSN XGDigital Enterprise Research Institute www.deri.ie  Semantic Sensor Networks ontology to describe sensors and sensor data  Semantic annotations for OGC’s SWE Sensor Model Language  Motivations  No existing sensor ontology included all the basic concepts  Ease integration of (some) semantics in more spread languages and standards (specifically SensorML) Enabling networked knowledge
  31. 31. Relation to existing standardsDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  32. 32. SSN-XG Ontology StructureDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  33. 33. SSN-XG Ontology StructureDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  34. 34. SSN Application: SPITFIREDigital Enterprise Research Institute www.deri.ie •DUL: DOLCE+DnS Ultralite •EventF: Event-Model F •SSN: SSN-XG •CC: Contextualised-Cognitive Concepts on sensor network topology and devices Sensor Datasets Event LOD Cloud Datasets Concepts on sensor role, events, sensor project Enabling networked knowledge
  35. 35. SPITFIRE VocabularyDigital Enterprise Research Institute www.deri.ie coalesenses http://www.spitfire-project.eu Enabling networked knowledge
  36. 36. Size matters!Digital Enterprise Research Institute www.deri.ie • OS + 6LowPAN + CoAP + Semantic description < 48kB? • Processing power? Enabling networked knowledge
  37. 37. Storage requirementsDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  38. 38. Digital Enterprise Research Institute www.deri.ie OK, we can describe sensors and their data now Enabling networked knowledge
  39. 39. RESTful sensor interfacesDigital Enterprise Research Institute www.deri.ie  Standardisation  Physical: 802.15.4  Network: IEEE 6LoWPAN, ROLL  Service layer: – IETF CoRE (Constrained RESTful Environments): CoAP protocol + extensions (very recent) – Encoding (Extensible XML interchange - EXI, SensorML) – Ontologies  CoAP = Constrained Application Protocol  IETF draft, http://tools.ietf.org/id/coap  Core proposal + > 17 extensions Enabling networked knowledge
  40. 40. CoAP = HTTP for sensorsDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  41. 41. CoAP ExampleDigital Enterprise Research Institute www.deri.ie Accessing sensors from we browser using HTTP-CoAP proxying – SPITFIRE Smart Service Proxy (SSP) Enabling networked knowledge
  42. 42. Digital Enterprise Research Institute www.deri.ie OK, we can access sensors via RESTful interfaces now Enabling networked knowledge
  43. 43. KISS revisitedDigital Enterprise Research Institute www.deri.ie Application CQELS REST SPARQL Linked Streams Linked Data Virtual COAP Sensors Sensors Enabling networked knowledge
  44. 44. CQELSDigital Enterprise Research Institute www.deri.ie  Continuous Query Evaluation over Linked Streams  Scalable processing model for unified Linked Stream Data and Linked Open Data  Combines data pre-processing and an adaptive cost-based query optimization algorithm  Experimental evaluation shows great performance (w.r.t. response time and scalability) Enabling networked knowledge
  45. 45. Black Box ApproachDigital Enterprise Research Institute www.deri.ie Query Query rewriter Optimizer SPARQL-like Operator implementations Orchestrator Overhead Executor Data transformation Execution Access methods Enabling networked knowledge
  46. 46. EP-SPARQL and C-SPARQLDigital Enterprise Research Institute www.deri.ie CSPARQL to SPARQL EP-SPARQL to Prolog Query Rewriter SPARQL Query Rewriter Engine Data transformation EP-SPARQL C-SPARQL Orchestrator Orchestrator RDF to Java objectsProlog Engine Data transformation RDF to prolog facts ESPER Data transformation Query Rewriter EP-SPARQL CSPARQL to EPSER EPL C-SPARQL Enabling networked knowledge
  47. 47. White Box ApproachDigital Enterprise Research Institute www.deri.ie Query Adaptive Optimizer Operator implementations Adaptive Executor Adaptive Execution Native Access methods RDF Linked dataset datastream Enabling networked knowledge
  48. 48. Enabling adaptivityDigital Enterprise Research Institute www.deri.ie  Incoming data will continuously change the costs of query plans ➥ Data elements are adaptively routed to processing operators on equivalent data flows (routing policies) Enabling networked knowledge
  49. 49. ExampleDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  50. 50. Processing Model: OperatorsDigital Enterprise Research Institute www.deri.ie  Triple-based window operators extracts triples from RDF stream or dataset that  match a given triple pattern  are valid within in a time window  Relational operators enable employing relational algebras in the processing model  Streaming operators generate new streams from output of other operators based on graph templates Enabling networked knowledge
  51. 51. Continuous Query Evaluation over Linked Streams (CQELS)Digital Enterprise Research Institute www.deri.ie Query CQELS language (an extension of SPARQL 1.1) Caching and Indexing Adaptive Optimizer Operator implementations Adaptive Executor Adaptive Execution SPO index scheme Dictionary Ring Triple-based Dynamic Routing Policy Native Access methods indices for windows RDF Linked dataset datastream Enabling networked knowledge
  52. 52. TechniquesDigital Enterprise Research Institute www.deri.ie  Dictionary encoding  Smaller memory for representing triples  Avoid lookup & decoding overhead for numeric RDF nodes  Caching and Indexing  Caching: avoid re-computing of intermediate results of sub- queries over non-stream data.  Indexing: facilitate faster access on caches and window data.  Dynamic Routing Policy  Incoming data can be evaluated in multiple equivalent data flows adaptive to changes  Easy & flexible support to implement routing policies Enabling networked knowledge
  53. 53. CQELS query languageDigital Enterprise Research Institute www.deri.ie CQELS Language – an extension to SPARQL 1.1 Construct new RDF stream Stream pattern Enabling networked knowledge
  54. 54. Experimental setupDigital Enterprise Research Institute www.deri.ie  Conference scenario: combine linked stream from RFID tags (physical relationships) with DBLP data (social relationships)  Setup  Systems: CQELS vs ETALIS and C-SPARQL  Datasets – Replayed RFID data from Open Beacon deployments – Simulated DBLP by SP2Bench  Queries: 5 query templates with different complexities – Q1: selection, – Q2: stream joins, Q3,Q4: Stream and non-stream joins – Q5: aggregation  Experiments – Single query: generate 10 query instances of each template by varying the constants – Vary size of DBLP dataset (104-107triples) – Multiple queries: register 2M parallel instances (0≤M≤10) Enabling networked knowledge
  55. 55. Experiment results - Query execution timeDigital Enterprise Research Institute www.deri.ie  CQELS performs faster by orders of magnitude Query 1 Query 2 Query 3 Query 4 Query5 CQELS 0.47 3.90 0.51 0.53 21.83 C-SPARQL 332.46 99.84 331.68 395.18 322.64 ETALIS 0.06 27.47 79.95 469.23 160.83 Aggregation: Simple selection: ETALIS performs best 15 times faster than C-SPARQL Stream join: Stream and non-stream joins: 8 times faster than ETALIS 25 times faster than C-SPARQL >600 times faster than C-SPARQL 8 times faster than ETALIS 150-850 times faster than ETALIS Enabling networked knowledge
  56. 56. Scalability: Static data sizeDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  57. 57. Scalability: # of queriesDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  58. 58. Next stepsDigital Enterprise Research Institute www.deri.ie  Optimization  Adaptive cost-based query optimization  Inter-query optimization  Smart and dynamic caching  Adaptive caching  Materialized view maintenance for dynamic data  Scalability: clusters and cloud Enabling networked knowledge
  59. 59. Digital Enterprise Research Institute www.deri.ie OK, now we can also process Linked Streams and integrate Linked Data efficiently Enabling networked knowledge
  60. 60. KISS revisitedDigital Enterprise Research Institute www.deri.ie Application CQELS REST SPARQL Linked Streams Linked Data Virtual COAP Sensors Sensors Enabling networked knowledge
  61. 61. RDF-on-the-go http://rdfonthego.googlecode.com/Digital Enterprise Research Institute www.deri.ie  A single, integrated mobile phone data store for all applications  Intrinsically integrated with the Web (Linked Data) Enabling networked knowledge
  62. 62. RDF-on-the-go http://rdfonthego.googlecode.com/Digital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  63. 63. Business Card DemoDigital Enterprise Research Institute www.deri.ie URI to FOAF file Enabling networked knowledge
  64. 64. Digital Enterprise Research Institute www.deri.ie OK, we can do all that on mobile phones too Enabling networked knowledge
  65. 65. KISS revisitedDigital Enterprise Research Institute www.deri.ie Application CQELS REST SPARQL Linked Streams Linked Data Virtual COAP Sensors Sensors Enabling networked knowledge
  66. 66. Global Sensor NetworksDigital Enterprise Research Institute www.deri.ie Decrease the cost and complexity of sensor network deployment  Abstraction level  Heterogeneous platforms  Abstract from data producers  Heterogeneous data  Data level  Semantic description of sensors and sensor data  No common abstractions  Data integration  Large scale  Very large scale  Distributed query processing and reasoning Enabling networked knowledge
  67. 67. Where are we now?Digital Enterprise Research Institute www.deri.ie Global Sensor Networks http://gsn.sourceforge.net/ WS • Uniform, declarative abstractions • Simple semantic descriptions SOA • Supports all major platforms • Fast and simple deployment • Plug & play GSN • Zero-programming • Efficient query processing Enabling networked knowledge
  68. 68. GSN’s view of the worldDigital Enterprise Research Institute www.deri.ie  Sensor network + base computer = sensor node  Many sensor nodes produce a lot of data on the Internet  Questions:  Deployment  Description  Discovery  Integration  Distributed processing Enabling networked knowledge
  69. 69. Central abstraction: Virtual sensorsDigital Enterprise Research Institute www.deri.ie  A virtual sensor can be any kind of data producer  a real sensor, a wireless camera, a mobile phone, etc. N input streams 1 (structured) output stream processing  a combination of other local or remote virtual sensors  Specification  simple semantic descriptions of sensors and data streams  declarative SQL-based specification of the data stream processing  functional properties related to stream quality management, etc. Enabling networked knowledge
  70. 70. Virtual sensor definition: XML + SQL Structure / data typeDigital Enterprise Research Institute Meta-data of output stream www.deri.ie <virtual-sensor name="room-monitor" priority="11"> <query> <addressing> select AVG(temp1) as T1 from WRAPPER <predicate key="geographical">BC143</predicate> </query> <predicate key="usage">room monitoring</predicate> </stream-source> </addressing> <stream-source alias="temperature2“ <life-cycle pool-size="10" /> storage-size="1m" <storage permanent="true" history-size="10h" /> disconnect-buffer-size="10"> <output-structure> <address wrapper="remote"> <field name="image" type="binary:jpeg" /> Input stream 2: <predicate key="type"> <field name="temp" type="int" /> System resources temperature Temperature </output-structure> </predicate> <input-streams> to assign <predicate key="geographical"> <input-stream name="cam"> BC143-S Query over input <stream-source alias="cam" storage-size="1" disconnect-buffer-size="10"> </predicate> </address> streams to produce <address wrapper="remote"> <query> output stream of <predicate key="geographical">BC143</predicate> select AVG(temp2) as T2 <predicate key="type">Camera</predicate> from WRAPPER the Virtual Sensor </address> </query> <query>select * from WRAPPER</query> </stream-source> </stream-source> <query> <stream-source alias="temperature1“ select cam.picture as image, temperature.T1 storage-size="1m" as temp disconnect-buffer-size="10"> from cam, temperature1 <address wrapper="remote"> where temperature1.T1 > 30 AND <predicate key="type">temperature</predicate> temperature1.T1 = temperature2.T2 <predicate key="geographical"> BC143-N Input stream 1: </query> </input-stream> Input stream 3: </predicate> </address> Camera images </input-streams> </virtual-sensor> Temperature70 of 58 Enabling networked knowledge
  71. 71. Accessing sensors: WrappersDigital Enterprise Research Institute www.deri.ie HTTP Generic Wrapper Generic UDP Wrapper  HTTP GET or POST requests  UDP connections Serial Forwarder Wrapper Generic Serial Wrapper Local RS-232 connections TinyOS compatible motes   TI-RFID Wrapper USB Camera Wrapper  Texas Instruments Series  Local USB connection 6000 S6700 multi-protocol RFID readers Bluetooth Wrapper  MAC and RFCOMM Bluetooth Generic RSS/XML Wrapper GPSD Wrapper COAP Wrapper  More than 60 NMEA-compliant GPS devices  RESTful interface to sensors  Contiki, Coalesenses Enabling networked knowledge
  72. 72. Coding effortsDigital Enterprise Research Institute www.deri.ie Wrapper type Lines of code TinyOS 120 WiseNode 75 Generic UDP 45 Generic serial 180 Wired camera 300 Wireless camera (HTTP) 60 RFID reader (TI) 50 Enabling networked knowledge
  73. 73. Selected FeaturesDigital Enterprise Research Institute www.deri.ie Workflow Editor - Web-based design of Virtual Sensors SafeStorage - Safe data backups Enabling networked knowledge
  74. 74. Plug and Play: Zero ProgrammingDigital Enterprise Research Institute www.deri.ie  An IEEE 1451-compliant sensor provides a Transducer Electronic Data Sheet (TEDS) which is stored inside the sensor  TEDS provides a simple semantic description of the sensor  the sensors properties and measurement characteristic  GSN uses the TEDS self-description feature for dynamic generation and deployment of virtual sensor descriptions  Next step: store queries not only data in TEDS or RFID tags New level of data processing in terms of flexibility Enabling networked knowledge
  75. 75. Digital Enterprise Research Institute www.deri.ie Does it really work? Enabling networked knowledge
  76. 76. Experimental setupDigital Enterprise Research Institute www.deri.ie  5 desktop PCs  Pentium 4, 3.2GHz with 1MB cache, 1GB memory, 100Mbit Ethernet, Debian 3.1  Linux kernel 2.4.27, MySQL 5.18  SN-1: 10 Mica2 motes with light and temperature sensors, packet size 15 Bytes, TinyOS  SN-2: 8 Mica2 motes with light, temperature, acceleration, and sound sensors, packet size 100 Bytes, TinyOS  SN-3: 4 Shockfish Tiny-Nodes with a light and two temperature sensors packet size 29 Bytes, TinyOS  SN-4: 15 wireless 8002.11b cameras (AXIS 206W), 640x480 JPEG, 5 with 16kB average image size, 5 with 32kB, 5 with 75kB  SN-5: TI Series 6000 S6700 multi- protocol RFID reader with three different kind of tags (up to 8KB of data) Enabling networked knowledge
  77. 77. Experimental setupDigital Enterprise Research Institute www.deri.ie  2 1.8 GHz Centrino laptops with 1GB memory as observers  Each ran up to 250 lightweight GSN instances.  Each instance produced random queries with varying table names, varying filtering condition complexity, and varying configuration parameters  3 filtering predicates in the WHERE clause on average, using random history sizes from 1 second up to 30 minutes and uniformly distributed random sampling rates (seconds) [0.01, 1]  Motes produce random bursts (1- 100 data items) with 25% probability Enabling networked knowledge
  78. 78. Processing time per clientDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  79. 79. Scalability in the number of clientsDigital Enterprise Research Institute www.deri.ie79 of 58 Enabling networked knowledge
  80. 80. Digital Enterprise Research Institute www.deri.ie OK, now we also have a nice middleware / database abstraction for any sensor type Enabling networked knowledge
  81. 81. KISS revisitedDigital Enterprise Research Institute www.deri.ie Application CQELS REST SPARQL Linked Streams Linked Data Virtual COAP Sensors Sensors Enabling networked knowledge
  82. 82. Digital Enterprise Research Institute www.deri.iePutting it all together Semantics / Linked Data / Real-Time / Streams / GIS Enabling networked knowledge
  83. 83. Linking the Real WorldDigital Enterprise Research Institute www.deri.ie People in DERI scan QR code with mobile to check into room Position of people in DERI  RFID tag of person is identified  FOAF info is displayed  Availability based on haptic phone interface QR code points to FOAF profile Associated RFID tag Associated mobile Available Not Available Position of other people In the demo room Enabling networked knowledge
  84. 84. Behind the ScenesDigital Enterprise Research Institute www.deri.ie www.deri.ie REST (FOAF) where.deri.ie REST gsn.deri.ie (FOAF) REST (availability) REST REST (position) (position) REST Screen (position, availability) Demo roomRFID base station Enabling networked knowledge
  85. 85. Digital Enterprise Research Institute www.deri.ie OK, now let’s make it bigger and general-purpose! Enabling networked knowledge
  86. 86. KISS re-re-visitedDigital Enterprise Research Institute www.deri.ie Application Middleware CQELS REST SPARQL Linked Streams Linked Data Virtual COAP Sensors Sensors Enabling networked knowledge
  87. 87. Linked Sensor MiddlewareDigital Enterprise Research Institute www.deri.ie  Middleware for the semantic integration of live real-world data  SPARQL endpoint for querying unified Linked Stream Data and Linked Data  Sensor mashup composer  Wrappers for collecting and enriching real-time / stream (sensor) data Live data  Web interface for data exploration, annotation and visualisation  Mobile phone applications Enabling networked knowledge
  88. 88. LSM ArchitectureDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  89. 89. Linked Stream ModelDigital Enterprise Research Institute www.deri.ie Sensor metadata :weatherStation ssn:observes ssn:observes :aTemperature ssn:observedBy :aHumidity ssn:isPropertyOf ssn:isPropertyOf :dublinAirport ssm:observedPropery ssm:observedPropery ssn:featureOfInterest :latestWeather :tempValue ssn:observationResult :humidValue ssn:hasValue ssn:hasValue ssm:value ssm:value ssm:unit ssm:unit :readings “18”^xsd:fl “60”^xsd:fl “Celcius” “%” oat oat Stream data snapshot at 2011-07-08T21:32:52 Enabling networked knowledge
  90. 90. Over 110,000 live data sourcesDigital Enterprise Research Institute www.deri.ie  Webcams:24570  Weather: 82365  Traffic:469 (London,  Snowfall: 2639 Ohio)  Snow depth: 377  Roadactivity:575 (Ohio)  Sea level: 45  Flights: >1000  Radar:1  Railway stations:251  Satellite: 12 (London)  Bike hire:421(London) … and growing!!! Enabling networked knowledge
  91. 91. DeploymentDigital Enterprise Research Institute www.deri.ie CQELS Web Virtuoso (Stream server Proc.) Data Bus Stream Sources Enabling networked knowledge
  92. 92. Mobile ApplicationsDigital Enterprise Research Institute www.deri.ie SPARQL,CQELS SPARQL-XML/RDF LSM 100-200 lines of code Enabling networked knowledge
  93. 93. LSM: Live flights infoDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  94. 94. LSM: Live train infoDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  95. 95. LSM: Live traffic infoDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  96. 96. http://lsm.deri.ieDigital Enterprise Research Institute www.deri.ie  A demo is worth a thousand words Enabling networked knowledge
  97. 97. LSM Example ApplicationDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  98. 98. LSM Example ApplicationDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  99. 99. LSM Example ApplicationDigital Enterprise Research Institute www.deri.ie Enabling networked knowledge
  100. 100. Digital Enterprise Research Institute www.deri.ie OK, what’s next? Enabling networked knowledge
  101. 101. Across Research AreasDigital Enterprise Research Institute www.deri.ie Semantic Web Linked Data Mobile Cloud Internet of Things Enabling networked knowledge
  102. 102. Strategic Application DomainsDigital Enterprise Research Institute www.deri.ie Smart Cities Enterprise Environments Telehealth Enabling networked knowledge
  103. 103. Upcoming Research AreasDigital Enterprise Research Institute www.deri.ie  Sensor data management in the Cloud  Sensor data annotation and sharing (portals, community-based)  Social network analysis (online, mobile, real-world)  Social and opportunistic sensing (mobile phone)  Distributed query processing  Integrating business processes and sensors Enabling networked knowledge 10 3
  104. 104. ConclusionsDigital Enterprise Research Institute www.deri.ie  “Linking the Real World” requires cross-domain / cross-layer research  Non-trivial, open research questions knowledge management, Semantic Web, databases, Cloud, sensor networks, etc.  Running systems and experiments! Enabling networked knowledge
  105. 105. AcknowledgementsDigital Enterprise Research Institute www.deri.ie  Danh Le-Phuoc  Anh Le Tuan  Myriam Leggieri  Hoan Nguyen Mau Quoc  Josiane Xavier Parreira  Martin Serrano  Christian von der Weth Enabling networked knowledge

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