Linked services for the Web of Data

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Keynote from the European Service Oriented and Cloud Computing Conference, Bertinoro, Italy

Keynote from the European Service Oriented and Cloud Computing Conference, Bertinoro, Italy

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  • 27 Live Video Steams for Olympics Live Stats overlaysStats -> Ontology driven aggregations
  • Open Graph Protocol Inspired by Dublin Core, link-rel canonical, Microformats, and RDFa.3,000,000 likes per day! ‘Like’ buttons now appearing across all websites. These now generate With associated data
  • 700 billion minutes per month on Facebook900 million content pages30 billion pieces of contentGenerating a graph of people, photos, friends and online resources
  • Supports RDFa Lite a lightweight version of RDFa which can be used to embed RDF into web pages
  • Google knowledge graphBased on Metaweb’s Freebase
  • 8665 datasets
  • 31billion statements, 450M links
  • So how do we link to this wealth of data?We have our own repository of service descriptions within the cloud. We are the first and still only service repository in this space. The are created using a variety of tools. Note that when creating our descriptions we can rely on existing descriptions in the cloud. In the same way as one web page can point to another to expand a description.
  • Which can produce data for this large semantic cloud
  • Now I come to a first of 3 examples. This one from a recent project. Imagine that you are moving to a new area and you are looking for a house. You would be concerned with
  • Depending on your circumstances
  • Within one of my projects (soa4all) we have developed an iPhone App to support this. Its available in the store and called the soa4all real estate finder
  • Mulberry school and others
  • Services over public data (to the singers in the virtual choir)Service broker is like the conductor. Services are published in our broker. An engine translates between user actions and details of invoking services (each service may have its own idiosyncratic way of being invoked)User interacts with the iPhone Appdiscovery based on user preferences and location -> services are available Services are not fixed (like singers for each performance). adding more for crime statistics also based on public data.
  • elasticity of heart muscles, another modelling blood flow, another for different dysfucntionsPatient avatar: a digital personalised representation of a patient for diagnosis and treatmentIn the media domainWe have a new project which started in Spring which will look at sharing processes related to the human body across Europe to support research and patient care. One of the processes to be modelled will be the human heart. The idea is that across varies labs in Europe there will be a bits and pieces of data and software – e.g. Our broker will be used to put these pieces together into a coherent whole and also to integrate into patient specific data leading to personalised patient avatars – a digital represention of your relevant processes supporting diagnosis and treatment.


  • 1. Linked Services for theWeb of DataJohn Domingue, Knowledge Media Institute,The Open University, UKSTI International, Austria
  • 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
  • 4. SemanticWebStack
  • 5. RDF = Subject, Property, ValueTriples
  • 6. Triples combine to make Graphs
  • 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,, 2006
  • 9. BBC Sports
  • 10. BBCSports
  • 11. BBCSports
  • 12.
  • 13. Live Video Streams
  • 14. I „Like‟ Casablanca
  • 15. People, photos, friends and theWeb
  • 16. Google Buys MetaWeb
  • 17. Freebase Data
  • 18. Application Portals
  • 19. Where does my money go?
  • 20. ASBOrometer
  • 21. Linked Open Data Cloud
  • 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. Web APIsJ. Mosser: “Open APIs: state of the market”, Glue conference 2011
  • 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
  • 28. MicroWSMO & WSMO-Lite 33
  • 29. Minimal Service Model
  • 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
  • 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. iServe Browser
  • 34. Linked Open Data Cloud
  • 35. iServe Context
  • 36. iServe Architecture
  • 37. SWEET
  • 38. SWEET Workflow
  • 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. Identifying Service Properties
  • 41. Semantic Annotation
  • 42. SWEET Architecture
  • 43. OMNIVOKE
  • 44. OmniVoke Context
  • 45. OmniVoke Architecture
  • 48. Example 1: House Hunting …
  • 49. … public transport …
  • 50. … schools
  • 51. Behind the ScenesPublic Data and Services Service Broker publishing Real estate discovery Train stations Bus stops Schools invocation
  • 52. WATCH’N’BUY
  • 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: tl:onTimeline ir:regionOf ma-ont: gr: foaf: dc: ma-ont:MediaResource time: tl: ir:
  • 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
  • 56. ParkJam 70
  • 57. Sharing Human Body Processes Personalised Patient Avatar ModelCardiovascular Workflow
  • 58. COMPOSE
  • 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:© SAP 2010 / Page 73
  • 60. USDL
  • 61. Linked-USDL
  • 62. Threats to Society
  • 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. Planetary Nervous Participatory System Platform Global high-level semantically meaningful information Living Earth Simulatorcomplex predictions (e.g “financial crisis likely”)
  • 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. Acknowledgements• BBC slides adapted from Jem Rayfield usergroup2012• Internet of Services adapted from SAP including Axel Fasse 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. Thanks• More details at:• Interested in a PhD Studentship or internship? –