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Linked services for the Web of Data

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Keynote from the European Service Oriented and Cloud Computing Conference, Bertinoro, Italy http://esocc2012.cs.unibo.it/

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Linked services for the Web of Data

  1. 1. Linked Services for theWeb of DataJohn Domingue, Knowledge Media Institute,The Open University, UKSTI International, Austria
  2. 2. Overview• Linked data introduction – Linked data successes• Linked Services – Approaches and principles – Technologies supporting Linked Services • Models: MicroWSMO, WSMO-Lite and the Minimal Service Model • Tools: iServe, SWEET and OmniVoke• Sample applications – House hunting – Integrating advertising and video in Watch‟n‟Buy• Current and future work• Summary
  3. 3. LINKED DATA INTRODUCTION
  4. 4. SemanticWebStack
  5. 5. RDF = Subject, Property, ValueTriples
  6. 6. Triples combine to make Graphs
  7. 7. Linked Data Principles Set of best practices for publishing structured data on the Web in accordance with the general architecture of the Web. 1. Use URIs as names for things. 2. Use HTTP URIs so that people can look up those names. 3. When someone looks up a URI, provide useful RDF information. 4. Include RDF statements that link to other URIs so that they can discover related things. Tim Berners-Lee, http://www.w3.org/DesignIssues/LinkedData.html, 2006
  8. 8. LINKED DATA SUCCESSES
  9. 9. BBC Sports
  10. 10. BBCSports
  11. 11. BBCSports
  12. 12. www.bbc.co.uk/ontologies/sport
  13. 13. Live Video Streams
  14. 14. I „Like‟ Casablanca
  15. 15. People, photos, friends and theWeb
  16. 16. Google Buys MetaWeb
  17. 17. Freebase Data
  18. 18. Application Portals
  19. 19. Where does my money go?
  20. 20. ASBOrometer
  21. 21. Linked Open Data Cloud
  22. 22. LINKED SERVICES
  23. 23. Linked Data and Services• Provide a platform for building applications on top of Linked Data• Connect services and semantic formats within the Web context• Ease the tasks associated with building applications from online service components
  24. 24. Web APIsJ. Mosser: “Open APIs: state of the market”, Glue conference 2011
  25. 25. LINKED SERVICES APPROACHAND PRINCIPLES
  26. 26. Linked Services Principles• Services described as Linked Data – Inputs, outputs, functionality, etc is described using RDF(S) and using existing vocabularies• Consume and produce RDF – Applications may contain „standard services‟ too• Process layer on top of the Web of Data
  27. 27. TECHNOLOGIES SUPPORTINGLINKED SERVICES
  28. 28. MicroWSMO & WSMO-Lite 33
  29. 29. Minimal Service Model
  30. 30. LPML Analysis &SWEET & SOWER deployment Discovery Monitoring Invocation Process Editor incl. BPEL-based execution environment incl. TG, Optimizer, DTC Process modeling Service Process annotation SOA4All execution Process Lifecycle
  31. 31. ISERVE SERVICE REPOSITORY
  32. 32. iServe Key Features • Support for several SWS formalisms – WSMO-Lite, MicroWSMO, SAWSDL, OWL-S • Supports access via – Web Application - iServe Browser – Read and Write RESTful API – Linked Data principles – SPARQL endpoint – Content negotiation (RDF, HTML) • Support for hybrid discovery • Integration of social features (tags, comments, ratings)
  33. 33. iServe Browser
  34. 34. Linked Open Data Cloud
  35. 35. iServe Context
  36. 36. iServe Architecture
  37. 37. SWEET
  38. 38. SWEET Workflow
  39. 39. SWEET: Initial StateCurrent status of theannotation in the form Input: HTML description of the Web API Addition ofof a tree structure (local representation of the HTML, which is the HTML tags used as a basis for the annotation process) Dynamics, APIs and Services / Hands-on SWEET/iServe and WSMT - 44
  40. 40. Identifying Service Properties
  41. 41. Semantic Annotation
  42. 42. SWEET Architecture
  43. 43. OMNIVOKE
  44. 44. OmniVoke Context
  45. 45. OmniVoke Architecture
  46. 46. TYPICAL APPLICATIONSCENARIO
  47. 47. SAMPLE APPLICATIONS
  48. 48. Example 1: House Hunting …
  49. 49. … public transport …
  50. 50. … schools www.tauntonschool.co.uk
  51. 51. Behind the ScenesPublic Data and Services Service Broker publishing Real estate discovery Train stations Bus stops Schools invocation
  52. 52. WATCH’N’BUY
  53. 53. Our Model gr:Offering wnb:reference wnb:Annotation wnb:annotates wnb:SpatioTemporalEntity gr:offers, gr:seeks, gr:saw dc:creator dc:created wnb:atTime wnb:atPosition time:Temporal ir:Region foaf:Agent xsd:dateTime Entity wnb: http://watchnbuy.kmi.open.ac.uk/ontologies/annotation# tl:onTimeline ir:regionOf ma-ont: http://www.w3.org/ns/ma-ont# gr: http://purl.org/goodrelations/v1# foaf: http://xmlns.com/foaf/0.1/ dc: http://purl.org/dc/elements/1.1/ ma-ont:MediaResource time: http://www.w3.org/2006/time# tl: http://purl.org/NET/c4dm/timeline.owl# ir: http://www.w3.org/2004/02/image-regions#
  54. 54. Architecture Watch n Buy Linked Data Provider Watch n Buy Player Watch n Buy Portal Watch n Buy Core Product Metadata Importer Video Metadata ImporterAnnotation User Review hProduct Amazon eBay YouTube TV Data Manager Manager Manager Importer Importer Importer Importer Importer Linked Services Infrastructure (iServe/OmniVoke) RDF Repository hProduct HTML hProduct
  55. 55. CURRENT AND FUTURE WORK
  56. 56. ParkJam 70 http://parking.kmi.open.ac.uk/
  57. 57. Sharing Human Body Processes http://www.vph-share.eu/ Personalised Patient Avatar ModelCardiovascular Workflow
  58. 58. COMPOSE
  59. 59. The Internet of Services – Unified Service Description Language (USDL)  Service Transformation stands for a value-driven, smooth and effective provision of services along the Global Service Delivery Supply Chain  Service Transformation implies that Services are being  Described considering business, operational and legal requirements  Maintained, extended and assembled where needed  Applying a common notation named USDL Service Service Service Service Service Service Provider Hoster Gateway Aggregator Broker Channel Maker See also: http://www.internet-of-services.de/index.php?id=24© SAP 2010 / Page 73
  60. 60. USDLhttp://www.internet-of-services.com/
  61. 61. Linked-USDLhttp://www.linked-usdl.org/
  62. 62. Threats to Society
  63. 63. A New Era of Socio-Inspired Technology New socially interactive Better understanding, ICT enabled by monitoring, complexity theory and and management of global novel social science society enabled by new ICT influencescomputer complexity social science science science influences
  64. 64. Planetary Nervous Participatory System Platform Global high-level semantically meaningful information Living Earth Simulatorcomplex predictions (e.g “financial crisis likely”)
  65. 65. Summary• Linked data now a mainstream mechanism for sharing data on the Web• Now a requirement for application development support – Especially within emerging Linked Data portals• Linked services – Services which consume and produce linked data – Described as Linked Data – Approaches and principles• Technologies supporting Linked Services • Models: MicroWSMO, WSMO-Lite and the Minimal Service Model • Tools: iServe, SWEET, OmniVoke….• Validation of approach through diverse application scenarios• Linked-USDL for services at the business level
  66. 66. Acknowledgements• BBC slides adapted from Jem Rayfield http://www.slideshare.net/JemRayfield/mark-logic- usergroup2012• Internet of Services adapted from SAP including Axel Fasse http://www.slideshare.net/drleidig/linked-usdl-at- the-fiware-architects-weeks-in-madrid• Chris Bizer, Jacek Kopecky, Ning Li, Dong Liu, Maria Maleshkova, Carlos Pedrinaci• Funded by the SOA4All, NoTube, PlanetData and VPH Share projects
  67. 67. Thanks• More details at: iserve.kmi.open.ac.uk• Interested in a PhD Studentship or internship? – John.domingue@open.ac.uk

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