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Breaking Down Walls in Enterprise with Social Semantics


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Keynote Talk at the Workshop on New Trends in Service Oriented Architecture for massive Knowledge processing in Modern Enterprise (SOA-KME 2012) / Palermo, Italy / 6th July 2012

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Breaking Down Walls in Enterprise with Social Semantics

  1. Breaking down walls in enterprise with social semantics John Breslin National University of Ireland, Galway
  2. Lecturer at NUI Galway Engineering and informatics
  3. • Researcher at DERI, NUI Galway
  4. Founder of the SIOC project• Semantically- Interlinked Online Communities• Enables interoperability and exchange of social content: – Blogs, forums, wikis...
  5. Co-founder of• Ireland’s largest discussion forum site• 2.25 million visitors/month• Irish people seeking information, or just chatting about sports, TV, politics, health, whatever
  6. Co-founder of StreamGlider, Inc.• Real-time streaming newsreader• Supports social, multimedia, news• Can be used as an enterprise dashboard
  7. Social platforms are like data silos image from
  8. Many isolated communities of users andtheir data image from
  9. Need ways to connect these islands image from
  10. Allowing users to easily travel from one toanother image from
  11. Enabling users to easily bring their data withthem image from
  12. Parallels in enterprise• Workers are using a variety of collaboration platforms internally in a localised or distributed enterprise• These platforms remain largely isolated from each other• Vast amounts of shared items and profiles are disconnected image from
  13. Object-centred sociality (AKA socialobjects)• Users are connected via a common object: – Their job, university, hobbies, interests, a date…• “According to this theory, people don’t just connect to each other. They connect through a shared object. […]Good services allow people to create social objects that add value.” – JyriEngestrom – Flickr = photos – = bookmarks – Blogs = discussion posts
  14. It’s the social objects we create…• Discussions• Bookmarks• Annotations• Profiles• Microblogs• Multimedia
  15. …that connect usto other people
  16. Semantics
  17. The Semantic WebA brief overview
  18. What’s in a page? And in a link? ? ? ?
  19. Tim Berners-Lee, The 1st World Wide WebConference, Geneva, May 1994 To a computer, the Web is a flat, boring world, devoid of meaning. This is a pity, as in fact documents on the Web describe real objects and imaginary concepts, and give particular relationships between them. […] Adding semantics to the Web involves two things: allowing documents which have information in machine-readable forms, and allowing links to be created with relationship values. Only when we have this extra level of semantics will we be able to use computer power to help us exploit the information to a greater extent than our own reading.
  20. Identifying resources with URIs• URIs are used to identify everything in a unique and non-ambiguous way: – Not only pages (as on the current Web), but any resource (people, documents, books, interests, etc.) – A URI for a person is different from a URI for a document about the person, because a person is not a document! – e.g.
  21. Defining assertions with RDF• URIs identify resources: – How do we define assertions about these resources?• We use RDF (Resource Description Framework): – A data model; a directed, labeled graph using URIs – Various serialisations (RDF/XML, N3, RDFa, etc.)• RDF is based on triples: – <subject><predicate><object> .
  22. RDF by example@prefix dct: <> .<>dct:title“Introduction to the Semantic Web” ;dct:author<> ;dct:subject <> .
  23. Defining semantics with ontologies• RDF provides a way to write assertions about URIs: – But what about the semantics of these assertions, e.g. to state that identifies an acquaintance relationship?• Ontologies provide common semantics for resources on the Semantic Web: – “An ontology is a specification of a conceptualization” – RDFS and OWL have different expressiveness levels
  24. Ontologies consist mainly of classes andproperties – :Person a rdfs:Class . – :father a rdfs:Property . – :father rdfs:domain :Person . – :father rdfs:range :Person .
  25. Linked Data• Building a “Web of Data” to enhance the current Web• Exposing, sharing and connecting data about things via dereferenceable URIs• The Linking Open Data (LOD) project: – – Translating existing datasets into RDF and linking them together, for example DBpedia (Wikipedia) and GeoNames, Freebase, BBC programmes, etc. – Government data available as Linked Data – LOD cloud in 2007:
  26. image
  27. Social semantic representationmodelsUsing ontologies to model social data
  28. Two-way street: the Semantic Web can helpsocial spaces, vice versa• Can use the Semantic Web to describe people, content objects and the connections that bind them all together so that social spaces can interoperate via semantics• In the other direction, object-centered social spaces can serve as rich social data sources for semantic applications image from
  29. The Social Semantic Web
  30. FOAFFriend Of A Friend
  31. What is FOAF?• An ontology for describing people and the relationships that exist between them: – – Identity, personal profiles and social networks – Can be integrated with other SW vocabularies• FOAF on the Web: – LiveJournal, MyOpera,, MyBlogLog, hi5, Fotothing, Videntity, FriendFeed, Ecademy, Typepad
  32. FOAF at a glance
  33. Distributed identity with FOAF
  34. FOAF from Flickr
  35. FOAF from Twitter
  36. Interlinking identities and networks
  37. SIOC, pronounced shock image from
  38. Semantically-Interlinked OnlineCommunities (SIOC)• Goal of the SIOC ontology is to address interoperability issues on the Social Web – – W3C member submission in 2007 – SIOC has been adopted in a framework of applications or modules deployed on hundreds of sites – Web 2.0, enterprise information integration, HCLS, e- government image from
  39. Some of the SIOC core ontology classesand properties
  40. Some applications using SIOC
  41. RDFa on
  42. RDFa in Drupal 7• Drupal CMS used by 2 percent of all sites• Drupal 7 release has Semantic Web support built-in• RDFa (SIOC, FOAF, Dublin Core, SKOS) data for blog posts, forums, etc.• Video at image from
  43. How much SIOC data is out there? images (this one and later backgrounds) from
  44. Sindice 2012: classes• Total instances of SIOC classes: 7.7M – Up 200k in three months• Most occurences: sioc:Item (2.2M) – Followed by: • UserAccount (1.6M), MicroblogPost (1.3M), Post (800k), User (700k), Comment (400k)... – Note: 1 billion foaf:Person instances!!!• Used on most [distinct] sites: – Item (7k), UserAccount (7k), Post (3k)...
  45. Sindice 2012: predicates• Total instances of SIOC predicates: 22.5M – Up 400k in three months• Most occurences: sioc:follows (4.6M) – Followed by: • topic (4M), account_of (3.5M), has_creator (2.7M), links_to (1.5M), has_discussion (1.3M)...• Used on most [distinct] sites: – has_creator (8k), num_replies (7k), name (2k), account_of (1.5k), reply_of (1.5k)...
  46. Sindice 2012: namespaces• SIOC data is being generated from 10k distinct domains (2k SLDs) (plus 2k domains for the SIOC Types module) – Increasing by about 100 domains a month – No doubt helped by Drupal!• FOAF data is being generated from 3M distinct domains (100k SLDs) – Increasing by over 1000 domains a month
  47. CommonCrawl• Muehleisen andBizer • Results published on – LDOW @ WWW 2012 Monday 2 July 2012• 1.5 billion web pages at:• 3 billion RDF quads • /vocabulary-usage-• SIOC available from analysis/index.html at least 22k PLDs (pay-level domains)• FOAF on 27k PLDs
  48. Online PresenceOntology (OPO)
  49. Tagging issues• Tagging enables user-generated classification of content with evolving and user-driven vocabularies• But it also raises various issues: – Tag ambiguity: • “apple” = fruit or computer brand? – Tag heterogeneity: • “socialmedia”, “social_media”, “socmed” – Lack of organisation: • No links between tags, e.g. “SPARQL” and “RDF”
  50. The Tag Ontology• The “Tag Ontology” by Newman from 2005: – – Based on Gruber’s tag model – tags:Tag rdfs:subClassOf skos:Concept – A “Tagging” class describing relationships between: • A user • An annotated resource • Some tags
  51. MOAT• MOAT (Meaning Of A Tag): – – A model to define “meanings” of tags – e.g. SPARQL → – User-driven interlinking – Tagged content enters the “Linked Data” web – Collaborative approach to share meanings in a community
  52. Tagging process with MOAT and DBpedia
  53. MOAT in Drupal
  54. Unifying collaborationsSome more semantically-enhanced systems, withenterprise applicability
  55. Semantic MediaWiki (SMW)
  56. Sample output from a SMW query
  57. Linking IRC to the Web of Data
  58. Mailing lists
  59. Bulletin boards
  60. SMOB
  61. Semantic #tagging• User-driven interlinking• Real-time URIs are suggested when writing content• Added ability to add new webservices (e.g. enterprise microblogging with contextual semantics)
  62. Distributedarch
  63. An ontology stack for social semanticcollaborative spaces
  64. Semantic Enterprise 2.0Enterprise 2.0 goes semantic
  65. Enterprise 2.0• Web 2.0 includes applications such as blogs, wikis, RSS feeds and social networking, while Enterprise 2.0 is the packaging of those technologies in both corporate IT and workplace environments: – Corporate blogging, wikis, microblogging – Social networking within organisations, etc.• “Enterprise 2.0 is the use of emergent social software platforms within companies, or between companies and their partners or customers” - McAfee, MIT Sloan, 2006
  66. Enterprise 2.0 and the Web• Many enterprises have an online presence on various Web 2.0 services to reach their customers: – Twitter – Slideshare – Facebook – Flickr – LinkedIn – etc.
  67. The SLATES acronym• Search: Easy and relevant access to information• Links: Enable better browsing capabilities between content• Authoring: Easy interfaces to produce content, in a collaborative way• Tagging: User-generated classification, enables serendipity and knowledge discovery• Extension: Recommendation of relevant content• Signals: Identify relevant content
  68. Social aspects of Enterprise 2.0• Enterprise 2.0 introduces new paradigms in organisations with regards to knowledge sharing and communication patterns: – Enterprise 2.0 is a philosophy• Enterprise 2.0’s success depends on a company’s background: – A study by AIIM showed that 41% of companies do not have a clear understanding of what Enterprise 2.0 is, while this percentage goes down to 15% in KM-oriented companies.
  69. Keys to Enterprise 2.0 adoption• Combining top-down and bottom-up approaches helps to realise Enterprise 2.0: – Top-down: Hierarchy (bosses!) sets up new tools and requires that various sections use them – Bottom-up: Users become evangelists and word-of- mouth improves the number of new users
  70. Business metrics for Enterprise 2.0• 13% of the Fortune 500 companies have a public blog maintained by their employees• Forrester Research predicts a global market for Enterprise 2.0 solutions of 4.6 billion dollars by 2013, and according to Gartner, more social computing platforms will be adopted by companies in next 10 years• Lots of companies and products in this space: – Awareness, Mentor Scout, SelectMinds, introNetworks, Jive Software, Visible Path, Web Crossing, SocialText, etc.
  71. Open-source applications• Open-source Web 2.0 apps can be efficiently used in organisations to build Enterprise 2.0 ecosystems: – Blogging: WordPress, etc. – Wikis: MediaWiki, MoinMoin, etc. – RSS readers and APIs: MagpieRSS, etc. – Integrated CMSs: Drupal, etc.
  72. Information fragmentation issues• Heterogeneity of people, services, needs and practices leads to various services and tools being deployed• By using various services (blogs, wikis, etc.), information about a particular object (e.g. a project) is fragmented over a company’s network: – Getting a global picture is difficult• Applications act as independent data silos, with different APIs, different data formats, etc.: – Data integration can be a costly task
  73. Lack of machine-readable data and taggingissues• Enterprise 2.0 enables and encourages people to provide valuable content inside organisations: – However, information is complex to re-use, generally remains locked inside services, and is for human- consumption only• Some queries cannot be answered automatically: – “List all the US-based companies involved in sustainable energies” – Plus there’s the aforementioned issue with tagging
  74. Semantic Web in enterprises• Semantic Web technologies are already widely used in organisations: – Ontology-based information management – Semantic middleware between databases – Intelligent portals – etc.• Semantic Web Education and Outreach (W3C): – – NASA, Lilly, Oracle, Yahoo!, etc.
  75. A Semantic Enterprise 2.0 architecture• Lightweight add-ons to existing applications to provide RDF data: – Exporters, wrappers, dedicated scripts, etc. – Taking into account the social aspect (e.g. semantic wikis)• Models to give meaning to this RDF data: – Domain ontologies, taxonomies, etc.• Applications on the top of it: – Thanks to RDF(S)/OWL and SPARQL
  76. The RDF Bus approach• RDF Bus architecture (Tim Berners-Lee): – Add-ons to produce RDF data from existing Web 2.0 applications• Store distributed data using RDF stores• Create new applications: – Semantic mashups – Semantic search• Open architecture thanks to a SPARQL endpoint, services as plugins to the architecture
  77. Relational DB to RDF mapping• Relational data (RDB) is structured data and can be mapped to RDF straightforward: – Allows integration of existing enterprise databases into the Semantic Enterprise 2.0 architecture• Main issues include: closed-world vs. open-world modeling; assigning URIs for entities (records); mapping language expressivity• For a state-of-the-art see veyReport.pdf
  78. LOD and Semantic Enterprise 2.0• Huge potential for internal IT infrastructures to enhance existing applications (mashups, extended UIs, etc.): – Integration of open and structured data from various sources at minor cost• Issue: dependance on external services, replication may be required• RSS is already widely used in organisations as a way to get information from the Web, LOD provides structured data to extend IT ecosystems
  79. Semantic Enterprise 2.0 use cases• Electricité De France R&D: – Integration of Enterprise 2.0 components using lightweight semantics• Ecospace EU project: – Interoperability of collaborative work environments• Boeing inSite: – Uses SIOC, FOAF and other social web standards to reduce time and effort spent finding and sharing
  80. Use case: EDF R&D
  81. Use case: CWE interoperability private folders BC semantic folder BSCW shadow folder
  82. Use case: Boeing inSite
  83. Related ongoing work
  84. SPARQL+XMPP+spreading activation forlinking enterprise collaborations (Cisco)
  85. Using PPO/PPM to access Linked(Enterprise) Data
  86. Aggregated, interoperable and multi-platform user profiles
  87. Summary• Object-centred sociality refers to how we really use social spaces: – Can use semantics to describe this usage, by representing objects for linkage and reuse• Applicability in the enterprise for collaboration platforms• Describe people, networks, content, presence, knowledge, tags, etc. with semantics• Providing solutions for novel uses in organisations: – Not just for the Social Web, but for Enterprise 2.0
  88. Acknowledgements• Thanks to my colleagues in the Unit for Social Software (USS) at DERI, especially for their slides!• We appreciate the support of Science Foundation Ireland and the Irish Research Council
  89. image from
  90. Our book… …at