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Linked services: Connecting services to the Web of Data

Date post: 11-May-2015
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Keynote from the International Conference on e-Business Engineering, September 2013. The talk covers a short integration to Linked Data, our approach to building applications on top of the Web of Data (which we term Linked Services) and a number of applications in the areas of house hunting: crowdsourcing car parking, sharing human body processes. The talk also covers recent work on transforming SAP's Unified Service Description Language to a Linked Data format.
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Linked Services: Connecting Services to the Web of Data John Domingue with Carlos Pedrinaci Knowledge Media Institute, The Open University
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  • 1.Linked Services: Connecting Services to the Web of Data John Domingue with Carlos Pedrinaci Knowledge Media Institute, The Open University

2. Overview Linked Data introduction Linked Data successes Linked Data applications Linked Services Approaches and principles Preliminary example Supporting tools and vocabularies Sample applications Sharing Human Body processes Crowdsourcing car parking Integrating advertising and video in WatchnBuy Service Marketplaces with Linked USDL Summary 3. LINKED DATA INTRODUCTION 4. Semantic Web Stack 5. RDF = Subject, Property, Value Triples 6. Triples combine to make Graphs 7. Linked Data Principles 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 Courtesy of Chris Bizer Set of best practices for publishing structured data on the Web in accordance with the general architecture of the Web. 8. LINKED DATA SUCCESSES 9. I Like Casablanca 10. People, photos, friends and the Web 11. LINKED DATA APPLICATIONS 12. (291) 13. Where does my money go? 14. ASBOrometer 15. Taken from http://ldif.wbsg.de/ 16. LINKED SERVICES APPROACH AND PRINCIPLES 17. 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 18. A PRELIMINARY EXAMPLE 19. Behind the Scenes Train stations Bus stops Schools Real estate Public Data and Services publishing Service Broker Invocation Engine discovery invocation 20. SUPPORTING TOOLS AND VOCABULARIES 21. SWEET & SOWER LPML deployment Process Editor Discovery incl. Optimizer Process Lifecycle Service annotation Process modeling Process execution Analysis & Monitoring incl. BPEL-based execution environment SPICES 22. LINKED SERVICE VOCABULARIES 23. WSDL 24. SAWSDL 25. WSMO-Lite Terms Ontology rdf:type rdfs:Class rdfs:subClassOf owl:Ontology ClassificationRoot rdfs:subClassOf rdfs:Class NonFunctionalParameter rdf:type rdfs:Class Condition rdf:type rdfs:Class Effect rdf:type rdfs:Class 26. RESTFUL SERVICES/WEB APIS 27. Microformat Collaboration with Amit Sheth Introduces the service model structure Service Operations Address, method Inputs, Outputs (only their existence) hRESTS 28. MicroWSMO Extends hRESTS mref for model references lifting, lowering Applies WSMO-Lite semantics 29. MicroWSMO & WSMO-Lite 30. Minimal Service Model, WSMO-Lite 31. Authentication 32. SUPPORTING TOOLS 33. ISERVE: A SEMANTIC SERVICE REPOSITORY 34. 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) 35. iServe Browser 36. Linked Open Data Cloud 37. iServe Architecture 46 38. iServe Service Discovery Several Mechanisms Simple SPARQL-based Inputs/Outputs logic-based using RDFS reasoning Functional Classifications with RDFS reasoning Similarity analysis based on iMatcher 39. iServe Discovery RESTful API /data/disco/func-rdfs?class=C1 &class=C2 &... uses RDFS functional classification annotations and returns those services that are related to all the functional categories Ci (which are URIs). /data/disco/io-rdfs?f={and|or}&i=C1I &i=C2I &o=C1O &... uses ontology annotations of inputs and outputs and returns services for which the client has suitable input data (CiI) and/or (depending on the parameter f for function) which provide the outputs requested by the client (CiO). /data/disco/imatch?name=L returns all services ranked according to the Levenshtein (other mechanisms available) string similarity of the service label with the string L. 40. iServe Atom-based Discovery Discovery returns an Atom feed with the results and provides Atom feed combinators - Union, Intersection, Subtract http://iserve.kmi.open.ac.uk/data/atom/union?f= /data/disco/func- rdfs?class=http://iserve.kmi.open.ac.uk/2010/05/s3eval/func.rdfs%2523ProximitySearch &f=/data/disco/io- rdfs?o=http://iserve.kmi.open.ac.uk/2010/05/s3eval/data.rdfs%2523ATMLocation 41. Integrated with a Recommender Distributed solution Linked User Feedback RS4All 42. SWEET: SEMANTIC WEB API ANNOTATION TOOL 43. SWEET Workflow 44. SWEET Demo (hRESTS) 45. SWEET Demo (Ontologies) 46. SWEET Architecture 47. SAMPLE APPLICATIONS 48. Sharing Human Body Processes PatientAvatar Personalised Model Cardiovascular Workflow 49. ParkJam 60 http://parking.kmi.open.ac.uk/ 50. Architecture RDF Repository Watch 'n' Buy Core Annotation Manager User Manager Review Manager Watch 'n' Buy Linked Data Provider Watch 'n' Buy Player Watch 'n' Buy Portal Product Metadata Importer hProduct Importer Amazon Importer eBay Importer Video Metadata Importer YouTube Importer TV Data Importer hProduct HTML hProduct Linked Services Infrastructure (iServe/OmniVoke) 51. Data Modelling Videos (Media) and their Fragments W3C Media Ontology: http://www.w3.org/TR/mediaont-10/ W3C Image Regions: http://www.w3.org/2004/02/image-regions (404ed) Watson cache of W3C Image Regions: http://kmi- web05.open.ac.uk:81/cache/d/6d9/d02c/1e2ba/66d39 a0e85/063395385293e283d W3C Media Fragment URIs: http://www.w3.org/TR/media-frags/ Annotation Open Annotation Collaboration: http://www.openannotation.org/spec/ 52. Our Model wnb:Annotation wnb:SpatioTemporalEntitywnb:annotates ir:Region gr:Offering wnb:reference wnb:atPosition ma-ont:MediaResource time:Temporal Entity foaf:Agent wnb:atTime tl:onTimeline ir:regionOf xsd:dateTime dc:createddc:creatorgr:offers, gr:seeks, gr:saw wnb: http://watchnbuy.kmi.open.ac.uk/ontologies/annotation# 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/ time: http://www.w3.org/2006/time# tl: http://purl.org/NET/c4dm/timeline.owl# ir: http://www.w3.org/2004/02/image-regions# 53. SERVICE MARKETPLACES 54. The Future Internet Enabler for Global Business Networks Manu- facturing Urban Management eEnergyTransport Logistic . Network of the Future Cloud Computing Internet of Things Internet of Services Internet of the Future Consumers Suppliers Wholesalers Retailers Carriers Manufacture r Governments SAP 2010 / 55. The Internet of Services Global Service Delivery Supply Chain A Single Market for Services SaaS, On-Demand Enterprise Suites Cloud Services Service Marketplaces Multi-Enterprise BPP B2B Gateways Business Process Outsourcing Business Process Platform Service Delivery Framework Service Aggregator Service Hoster Service Provider Service Gateway Service Broker Service Channel Maker Service-Oriented Architecture SAP 2010 / Page 67 56. SAP 2010 / Page 68 Service Aggregator Service Hoster Service Provider Service Gateway Service Broker Service Channel Maker The Internet of Services Unified Service Description Language (USDL) See also: http://www.internet-of-services.de/index.php?id=24 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 57. TRESOR 58. Summary (1/2) Linked Data Based on 4 simple principles Take-up now by major Web and Media players Linked Data portals now emerging Lack of support for applications Linked Services Approach to creating applications on top of Linked Data Built upon Vocabularies: Minimal Service Model, MicroWSMO, WSMO-Lite Tools: iServe, SWEET 59. Summary (2/2) Linked service applications include: SOA4RE for house hunting ParkJam supporting crowd-sourced car park availability Towards patient avatars Linked USDL for Service Marketplaces 60. Credits and URIs iServe - http://iserve.kmi.open.ac.uk/ Linked USDL - http://www.linked-usdl.org/ SOA4All funded under FP7 - http://www.soa4all.eu/ VPH-Share funded under FP7 - http://www.vph- share.eu/ ParkJam - http://parking.kmi.open.ac.uk/ Also based on work of: Jacek Kopecky, Dong Liu, Maria Maleshkova


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