1. www.1spatial.com © 1Spatial 2010. All rights reserved. An Internet of Places Making Location Data Pervasive Paul Watson Giuseppe Conti* Federico Prandi* * Fondazione Graphitech

2. Role of Spatial Information  Location critical to our understanding and model of the world  Navigation  Land & Property Management  Environment & Natural Resources  Asset Management  Retail (Logistics/Store Planning)  Defence & Intelligence  Insurance  £100 billion of business per annum underpinned by spatial data in UK alone

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4. Internet of Places

5. 5 PointMultiPointLineStringMultiLineString PolygonPolygon (holes)MultiPolygonCollection

6. Use Case 6

7. Objectives  Spatio-temporal fabric for Web content  Discover content from all sources – real-time/static  “Spatialise” existing Web content  Allow spatio-temporal data to merge with other data  Bridge structured, semi-structured and unstructured data  Change metaphor from keyword search to virtual exploration  Manufacture (join) spatio-temporal data on-demand  Present spatio-temporal data useably (devices) 7

8. Dependencies  Common data model for spatio-temporal and all other data  Semantic spatio-temporal search (space – time – task)  Flexible data enrichment services  Flexible data adaptation services  Orchestration services  Augmented reality & Semantic 3D GeoBrowsers  many commonalities with SOA-based spatial data supply chain 8

9. Semantic Web - Vision  The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. (2001)  The first step is putting data on the Web in a form that machines can naturally understand, or converting it to that form. This creates what I call a Semantic Web – a web of data that can be processed directly or indirectly by machines. – Weaving the Web (2000) 9

10. Linked Data - Definition  A method of exposing, sharing, and connecting data via dereferenceable URIs on the Web.  Use URIs (web addresses) as names for things (e.g. Cambridge)  Use HTTP URIs so that people can look up those names  When someone looks up a URI, provide useful information, using the standards (RDF, SPARQL)  Include links to other URIs. so that they can discover more things  Berners-Lee, Tim. W3C Design Note – Linked Data, 2006, http://www.w3.org/DesignIssues/LinkedData.html http://www.w3.org/DesignIssues/LinkedData.html

11. RDF & SPARQL  RDF - Machine-readable, triples (subject-predicate-object – all URI’s)  Subject:Cambridge – Predicate:isInCounty – Object:Cambridgeshire  Single uniform data model for all information  Look up every URI in an RDF graph over the Web  Information merges naturally  Set RDF links between data from different sources  Represent scattered information in a single model  Schema languages (RDF-S & OWL) allow tightly structured data, unstructured data or anything in between  SPARQL - W3C Query language and protocol to select parts of RDF graphs  globally unambiguous queries SubjectObject Predicate

12. Redirection & Content Negotiation  Document web and data web need to co-exist using HTTP  Information and non-information resources  Client specifies preferred content type

13. Linked Data Relationship to Semantic Web  Futureproofing data access  Compatibility with machine reasoning (RIF, OWL)  “Upgrade” existing data sources with new “firmware”

14. Why Linked Data?  Equally applicable to unstructured, semi-structured, and structured data and content  Elimination of internal data 'silos'  Automatic Integration of internal and external data  Easy linking of enterprise, industry-standard, open public and public subscription data  Complete data modelling of any legacy schema  Flexible and easy updates and changes to existing schema  An end to the need to re-architect legacy schema resulting from changes to the business or M & A  Report creation and data display based on templates and queries, not requiring manual crafting  Flexible data access, analysis and manipulation - user level  Internal linked data stores can be maintained by existing DBA procedures and assets

15. Linking Open Data cloud diagram

16. Web Information Retrieval

17. Limitations of Keyword Search  Requires that search can be expressed in pre-arranged keywords e.g. Olympic Games  Inadequate for concepts which are not readily expressible in keywords, like time & space e.g. events within 10 miles of Cambridge city centre, in the last 30 mins  Returns whole documents  Not “joined up” – manual integration  Rudimentary presentation – not contextual  But – contrast the traditional SDI approach (Cathedral not Bazaar) 17

18. GeoCrawling & Indexing 18 Tags Africa Precipitation

19. Flexible Semantic Search – finding tags 19 Relevant ontology set Inferred from user’s task

20. Recognising Implicitly Spatio-temporal Content 20

21. Geoparsing 21

22. Federated Search - DNS 22 Data Expiry Sensors Social Master B2B Dynamic Static

23. Presentation 23

24. Content Adaptation 24 Rich clientNavigation Raster Only Thin client

25. Conceptual Architecture 25

26. unlocking data, empowering business thank you for listening