The document discusses the Social Semantic Web and related technologies. It provides an overview of the growth of social networks and user-generated content online. It then discusses how semantic technologies can help connect isolated social communities and their data by adding machine-readable metadata. Key topics covered include the Semantic Web stack, linked data, ontologies for modeling social data like FOAF and SIOC, and applications like distributed identity and social recommendations.

1. The Social Semantic Web:ICWSM TutorialAlexandre PassantJohn Breslin

2. IntroductionWhy is this important?

3. The Social Webis exploding!image from tinyurl.com/nuketest

4. 61% = social networks11% = forums11% = UG content sites, e.g. urbandictionary.com10% = UG marketplaces, e.g. craigslist.org03% = blogs01% = UG reviews, e.g. apartmentratings.com01% = wikis02% = othertext from tinyurl.com/briscougc

5. Sites go up...image from tinyurl.com/rocket15

6. Facebook and Twitter

7. ...and sites come downimage from tinyurl.com/elhell

8. Bebo

9. Object-centred sociality (AKA social objects) gives some explanationsUsers 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.” – JyriEngestromFlickr = photosdel.icio.us = bookmarksBlogs = discussion posts

10. It’s the social objects we create…DiscussionsBookmarksAnnotationsProfilesMicroblogsMultimedia

11. …that connect usto other people

12. Boom!

13. image from tinyurl.com/orionwThe amount of stuff out there is vast

14. Social websites are like data silosimage from pidgintech.com

15. Many isolated communities of users and their dataimage from pidgintech.com

16. Need ways to connect these islandsimage from pidgintech.com

17. Allowing users to easily move from one to anotherimage from pidgintech.com

18. Enabling users to easily bring their data with themimage from pidgintech.com

19. Semantics

22. The Semantic WebA brief overview

23. What’s in a page ? And in a link ????

24. Tim Berners-Lee, The 1st World Wide Web Conference, 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.

25. Aims of the Semantic WebBridging the gap between a Web of Documents to a Web of Data, with typed objects and typed relationshipsAdding machine-readable metadata to existing content, so that information can be parsed, queried, reusedDefining shared semantics for this metadata to allow interoperability between applications and for advanced purposes, such as reasoningEnabling machine-readable knowledge at Web scale, making information more easy to find and process

26. A bit of historyMemex, Vannevar Bush, 1945:“A device in which an individual stores all his books, records, and communications.”Augmenting Human Intellect, Douglas Engelbart, 1960: “By ‘augmenting human intellect’ we mean increasing the capability of a man to approach a complex problem situation, to gain comprehension to suit his particular needs, and to derive solutions to problems.”

27. The Semantic Web, circa 2010Most standardisation work is done in the W3C:http://www.w3.org/The Semantic Web activity:http://www.w3.org/2001/sw/Incubator Groups, Working Group, Interest Groups:WGs for SPARQL, RDB2RDF, RIF, etc.HCLS IG, Social Web XG, etc.

28. image from www.w3.org/2007/03/layerCake.pngThe Semantic Web stack

29. Identifying resources with URIsURIs 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. http://dbpedia.org/resource/Galway

30. Defining assertions with RDFURIs identify resources:How do we define assertions about these resources?We use RDF (Resource Description Framework):A data model; a directed, labeled graph using URIsVarious serialisations (RDF/XML, N3, RDFa, etc.)RDF is based on triples:<subject> <predicate> <object> .

31. RDF by example@prefix dct: <http://purl.org/dc/terms/> . <http://example.org/dm110-semweb>dct:title“Introduction to the Semantic Web” ;dct:author <http://apassant.net/alex> ;dct:subject <http://dbpedia.org/resource/Semantic_Web> .

32. RDFaA way of embedding RDF in (X)HTML documents:One page for both humans and machinesDon’t need to repeat yourselfIntroducing new XHTML attributesCurrent work is ongoing on RDFa 1.1:For profiles, etc.

33. RDFa example

34. Defining semantics with ontologiesRDF provides a way to write assertions about URIs:But what about the semantics of these assertions, e.g. to state that http://xmlns.com/foaf/0.1/knows 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

35. Ontologies consist mainly of classes and properties:Person a rdfs:Class .:father a rdfs:Property .:father rdfs:domain :Person .:father rdfs:range :Person .

36. Metadata and ontologies

37. Notable ontologiesSocial networks and social data: FOAF, SIOCSoftware development: DOAP, BEATLEComprehensive / top-level: Yago, OpenCYCTaxonomies and controlled vocabularies: SKOS

38. Linked DataBuilding a “Web of Data” to enhance the current WebExposing, sharing and connecting data about things via dereferenceable URIsThe Linking Open Data (LOD) project:http://linkeddata.org/Translating existing datasets into RDF and linking them together, for example DBpedia (Wikipedia) and GeoNames, Freebase, BBC programmes, etc.Governement data also available as Linked Data

39. The LOD cloud20072008

40. The LOD cloud20082009

41. image from richard.cyganiak.de/2007/10/lod/lod-datasets_2009-07-14.png

42. Representation models for the Social Semantic WebUsing ontologies to model social data

43. Semantics can help social websites, and vice versaBy using agreed-upon semantic formats to describe people, content objects and the connections that bind them all together, social media sites can interoperate by appealing to common semanticsDevelopers are already using semantic technologies to augment the ways in which they create, reuse, and link profiles and content on social media sites (using FOAF, XFN / hCard, SIOC, etc.)In the other direction, object-centered social networks can serve as rich data sources for semantic applications

44. The Social Semantic Web

45. FOAFFriend Of A Friend

47. FOAF (Friend-of-a-Friend)An ontology for describing people and the relationships that exist between them:http://foaf-project.org/Identity, personal profiles and social networksCan be integrated with other SW vocabulariesFOAF on the Web:LiveJournal, MyOpera, identi.ca, MyBlogLog, hi5, Fotothing, Videntity, FriendFeed, Ecademy, Typepad

48. FOAF (Friend-of-a-Friend)

49. FOAF (Friend-of-a-Friend)

50. FOAF at a glance

51. FOAF from Flickr

52. FOAF from Twitter

53. Exporting FOAF dataFacebook:http://www.dcs.shef.ac.uk/~mrowe/foafgenerator.htmlTwitter:http://semantictweet.com/Flickr:http://apassant.net/blog/2007/12/18/rdf-export-flickr-profiles-foaf-and-sioc/And many more (Drupal 7, WordPress plug-ins, etc.)

54. Distributed identity with FOAF

55. Interlinking identities and networks

56. Cross-site social recommendations with FOAF

57. Distributed authentication with FOAF+SSL

58. SIOCSemantically-Interlinked Online Communities

59. SIOC, pronounced shockimage from tinyurl.com/siocshock

60. Semantically-Interlinked Online Communities (SIOC)An effort from DERI, NUI Galway to discover how we can create / establish ontologies on the Semantic WebGoal of the SIOC ontology is to address interoperability issues on the (Social) Webhttp://sioc-project.org/SIOC has been adopted in a framework of 50 applications or modules deployed on over 400 sitesVarious domains: Web 2.0, enterprise information integration, HCLS, e-government

61. 61The aims of SIOCTo “semantically-interlink online communities”To fully describe content / structure of social websitesTo create new connections between online discussion posts and items, forums and containersTo enable the integration of online community infoTo browse connected Social Web items in interesting and innovative waysTo overcome the chicken-and-egg problem with the Semantic Web

63. Some of the SIOC core ontology classes and properties

64. 64

65. Designed to fit with other ontologies

66. Combining SIOC and FOAF

68. 68From last October

69. SIOC and other RDFa in Drupal 7Drupal is a CMS used by whitehouse.gov, warnerbrosrecords.com, uk.sun.com, motogp.com... Two alpha versions of Drupal 7 released already, Semantic Web support built-in (RDFa)Full version expected soon

70. Semantic search

71. 71

72. 72Find out more about the SIOC project

73. Semantic presenceModeling presence and status updates using semantics

74. MotivationsThere is a need to unify presence information and status notification processes across different services:Twitter, Facebook, Foursquare, etc.We can solve the information overload issue at the same time, by providing a means to identify who / which community the information should reach

75. Online PresenceOntology@@ TODO

76. The OPO model

77. Sharing spaces allow us to…Solve the identity fragmentation problem related to status messages sharing:We may not want to share the same information to different peopleModel whom information is directed to:e.g. “Social media-aware people”, “Family contacts”, “Good friends”, “Work colleagues”, etc.Build with OPO, using rules defined in SPARQL, the query language for RDF

78. @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.@prefix opo: <http://ggg.milanstankovic.org/opo/ns#>.@prefix foaf: <http://xmlns.com/foaf/0.1/>.@prefix sioc: <http://rdfs.org/sioc/ns#>.:Fred rdf:typefoaf:Agent;foaf:mbox <mailto:fred@gmail.com>.:myCustomMessagerdf:typesioc:Post;sioc:content "anybody in for a drink tonight?".:MyCurrentPresencerdf:typeopo:OnlinePresence;opo:customMessage :myCustomMessage;opo:startTime "2008-03-01T18:51:19";opo:intendedFor<http://example.org/FamilyFriendsBedrock>:Betty opo:declaresOnlinePresence :MyCurrentPresence.

79. @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.@prefix opo: <http://ggg.milanstankovic.org/opo/ns#>.@prefix foaf: <http://xmlns.com/foaf/0.1/>.@prefix sioc: <http://rdfs.org/sioc/ns#>.:Fred rdf:typefoaf:Agent;foaf:mbox <mailto:fred@gmail.com>.:myCustomMessagerdf:typesioc:Post;sioc:content "anybody in for a drink tonight?".:MyCurrentPresencerdf:typeopo:OnlinePresence;opo:customMessage :myCustomMessage;opo:startTime "2008-03-01T18:51:19";opo:intendedFor <http://example.org/FamilyFriendsBedrock>:Betty opo:declaresOnlinePresence :MyCurrentPresence.PREFIX foaf: <http://xmlns.com/foaf/0.1/>PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>PREFIX rel: <http://purl.org/vocab/relationship>CONSTRUCT{ <http://example.org/ns#FamilyFriendsBedrock> rdf:typeopo:SharingSpace;foaf:member?person.}WHERE{ { ?person rel:friendOf_ <http://flintstones.org/Fred> } UNION { ?person rel:spouseOf_ <http://flintstones.org/Fred> } UNION { ?person rel:childOf_ <http://flintstones.org/Fred> } . ?person foaf:basedNear <http://imaginary.geonames.org/bedrock/> .}

80. Semantic taggingBridging the gap between folksonomies and ontologies

81. Tagging issuesTagging enables user-generated classification of content with evolving and user-driven vocabulariesBut 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”

82. Use case illustrating such issuesCorporate use case > 3 years, 12257 tags, 21614 posts:54.2% of tags used once, 75.77% used <= 3 timesLots of valuable information lost in the long tailTagging and expertise gap:194 items tagged with “TF” (= Thin Film)1% of them tagged with “solar”< 0.5% of “solar” items tagged “TF”Both tags are weakly related from a co-occurrence point of view, clustering cannot be efficiently used

83. The long tail of tags

85. The Tag OntologyThe “Tag Ontology” by Newman from 2005:http://www.holygoat.co.uk/projects/tags/Based on Gruber’s tag modeltags:Tag rdfs:subClassOf skos:ConceptA “Tagging” class describing relationships between:A userAn annotated resourceSome tags

86. SCOTSCOT (Social Semantic Cloud of Tags):http://scot-project.org/A model to describe tagclouds (tags and co-occurrence)Ability to move your own tagcloud from one service to anotherShare tagclouds between services, and between users“Tag portability”

87. MOATMOAT (Meaning Of A Tag):http://moat-project.org/A model to define “meanings” of tagse.g. SPARQL ->http://dbpedia.org/resource/SPARQLUser-driven interlinkingTagged content enters the “Linked Data” webCollaborative approach to share meanings in a community

88. MOAT with DBpedia example data

89. Tagging process with MOAT and DBpedia

90. MOAT in Drupal

91. CommonTagCommonTag:http://commontag.org/A joint effort by AdaptiveBlue, DERI at NUI Galway, Faviki, Freebase, Yahoo!, Zemanta and ZigtagLinking tags to meaningful resource (à la MOAT)

92. Life cycle for CommonTag data

93. NiceTagNiceTag Ontology:Tagging meets speech act theoryFocus on the link between a tag and a tagged item

94. Extracting ontologies from tagsFolksOntology:Semi-assisted extraction of relationships between tagsFLOR:FoLksonomy Ontology enRichmenthttp://flor.kmi.open.ac.uk/Automated approach to identify tag meaningsCan be combined with the previous models for a complete semantic tagging stack

96. Mining hierarchical relationships from co-occurrence of tags by Halpin et al.

97. LODr: semantic tagging for social data

98. Faviki: bookmarking meets DBpedia

99. Unifying conversationsSome more semantically-enhanced systems

100. Linking IRC to the Web of Data

101. Mailing lists

102. 102Bulletin boards

103. SMOB

104. Distributedarch

105. An ontology stack for microbloggingCombining the previous vocabularies for a complete representation of microblogging and microblogging activitiesEach microblog post is available in RDF (RDFa + raw RDF) on the publisher’s hub, using these models

106. Semantic #taggingUser-driven interlinkingReal-time URIs are suggested when writing contentAdded ability to add new webservices (e.g. enterprise microblogging)

107. Semantic microblogging mashups

108. SPARQLing Social Semantic Web dataFind all posts and their titles by John, using SELECT, and combining vocabularies (DC, SIOC, SIOC Types):SELECT ?post ?titleWHERE { ?post rdf:type sioct:BlogPost ; dc:title ?title ; sioc:has_creator <$johns_URI> .}

109. SPARQLing Social Semantic Web data (2)Find all users that posted replies to John’s blog since January 2008, introducing the FILTER clause:SELECT ?whoWHERE { ?post rdf:type sioct:BlogPost ; dc:title ?title ; sioc:has_creator <$johns_URI> . ?post sioc:has_reply ?reply . ?reply sioc:has_creator ?who ; dcterms:created ?date . FILTER (?date > "2008-01-01T00:00:00Z"^^xsd:dateTime)}

110. SPARQLing Social Semantic Web data (3)Find all content created by someone with a given OpenID URL:Browse someone’s social media contributions posted on various websites using different account names, but for the same personSELECT ?itemWHERE { ?person foaf:openid <$openid> ; foaf:holdsAccount ?user . ?user sioc:creator_of ?item .}

111. Parse SPARQL resultsSPARQL XMLJSON:EasiestMany extensions (e.g. PHP5)Many examples

112. Querying RDF filesRedland: http://librdf.orgBindings: Available for PHP, Python, etc.Example in Python:Import RDFm = RDF.Model()m.load(‘http://apassant.net/foaf.rdf’)q = RDF.Query("SELECT ?s WHERE { ?s ?p ?o .}")results = q1.execute(model)for result in results: print result[’s']

113. Need more data?Translate any data to SIOC:Re-use SIOC tools for non-SIOC dataSemantic Pipes:http://pipes.deri.org/SPARQL constructs:The “XSLT” of RDF; translate a set of RDF data from one graph format to anotherCONSTRUCT { ?x a sioc:Post . ?xsioc:has_creator ?y }WHERE { ?x a myont:BlogElement . ?xmyont:created_by ?y }113

114. From data to knowledgeSemantic wikis

115. Issues with traditional wikisStructured accessInformation reuseMade for humans, not machinesJohnGrishamHe is the author of PelicanBrief.He lives in Mississippi.He writes a book each year.He is published by RandomHouse.Structured access:Other books by JohnGrisham (navigation)

116. All authors that live in Europe? (query)Information reuse:The authors from RandomHouse (views)

117. And what if I don't speak English? (translation)Semantic wikisCapture some information about the pages in a formal language, letting machines process and reason on it:Some systems focus on metadata about the content, some on the social aspect, some on bothA semantic wiki should be able to capture that an article about SPARQL is related to the Semantic Web and present you with further related informationVarious use cases and prototypes:http://www.semwiki.org/

118. From wikis to semantic wikis

119. Structure / content

120. SemperWiki

121. Semantic MediaWikiAn extension of MediaWiki, allowing users to add structured information to pages:Classifying links, e.g. making a relationship such as “capital of” between Berlin and Germany explicit:... [[capital of::Germany]] ... resulting in the semantic statement "Berlin" "capital of" "Germany"Defining assertions:... the population is [[population:=3,993,933]] ... resulting in the semantic statement "Berlin" "has population" "3993933"Currently the most widely-deployed semantic wiki

122. Input using Semantic MediaWiki

123. One possible output from a SMW query

124. IkeWiki

125. UfoWiki

126. FromWikipedia…

127. …to DBpedia@@ TODO

128. DBpedia mobile

129. Semantic social networksUsing semantics in the analysis of social networks and social websites

130. SNA with semanticsCombining ontologies, folksonomies and SNA:Mika, “Ontologies Are Us”, ISWC 2005Ontology and SPARQL extensions for common SNA patterns:Ereteo et al., ISWC 2009SPARQL extensions (most are now in SPARQL 1.1):San Martin et al., ESWC 2009

131. boards.ie use case10 years of conversations, 150k users, 7M posts:Analysing the structured data that people link toTo appear in Kinsella et al., i-Semantics 2010

132. From raw data to rich data

134. Some of the main sources of structured data

135. New possibilities for SNA and SMA

136. Semantic Enterprise 2.0Enterprise 2.0 goes semantic

137. Some serious applications for Web 2.0Web 2.0 in research environments:Using wikis for project proposalsScientific community blogging (e.g. Nature Network)

138. Enterprise 2.0Web 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, microbloggingSocial 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

139. Enterprise 2.0 and the WebMany enterprises have an online presence on various Web 2.0 services to reach their customers:TwitterSlideshareFacebookFlickrLinkedInetc.

140. The SLATES acronymSearch: Easy and relevant access to informationLinks: Enable better browsing capabilities between contentAuthoring: Easy interfaces to produce content, in a collaborative wayTagging: User-generated classification, enables serendipity and knowledge discoveryExtension: Recommendation of relevant contentSignals: Identify relevant content

141. Social aspects of Enterprise 2.0Enterprise 2.0 introduces new paradigms in organisations with regards to knowledge sharing and communication patterns:Enterprise 2.0 is a philosophyEnterprise 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.

142. Keys to Enterprise 2.0 adoptionCombining 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 themBottom-up: Users become evangelists and word-of-mouth improves the number of new users:http://strange.corante.com/2006/03/05/an-adoption-strategy-for-social-software-in-enterprisehttp://many.corante.com/archives/2004/10/27/middlespace.php

143. Business metrics for Enterprise 2.013% of the Fortune 500 companies have a public blog maintained by their employeesForrester 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 yearsLots of companies and products in this space:Awareness, Mentor Scout, SelectMinds, introNetworks, Jive Software, Visible Path, Web Crossing, SocialText, etc.

144. 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.

145. Information fragmentation issuesHeterogeneity of people, services, needs and practices leads to various services and tools being deployedBy 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 difficultApplications act as independent data silos, with different APIs, different data formats, etc.:Data integration can be a costly task

146. Lack of machine-readable data and tagging issuesEnterprise 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 onlySome queries cannot be answered automatically:“List all the US-based companies involved in sustainable energies”Plus there’s the aforementioned issue with tagging

147. Semantic Web in enterprisesSemantic Web technologies are already widely used in organisations:Ontology-based information managementSemantic middleware between databases Intelligent portalsetc.Semantic Web Education and Outreach (W3C):http://www.w3.org/2001/sw/sweo/public/UseCases/NASA, Eli Lilly, Oracle, Yahoo!, Sun, etc.

148. A Semantic Enterprise 2.0 architectureLightweight 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

149. The RDF Bus approachRDF Bus architecture (Tim Berners-Lee):Add-ons to produce RDF data from existing Web 2.0 applicationsStore distributed data using RDF storesCreate new applications:Semantic mashupsSemantic searchOpen architecture thanks to a SPARQL endpoint, services as plugins to the architecture

150. Relational DB to RDF mappingRelational data (RDB) is structured data and can be mapped to RDF straightforward:Allows integration of existing enterprise databases into the Semantic Enterprise 2.0 architectureMain issues include: closed-world vs. open-world modeling; assigning URIs for entities (records); mapping language expressivityFor a state-of-the-art see http://www.w3.org/2005/Incubator/rdbrdf/RDB2RDF_SurveyReport.pdf

151. LOD and Semantic Enterprise 2.0Huge potential for internal IT infrastructures to enhance existing applications (mashups, extended UIs, etc.):Integration of open and structured data from various sources at minor costIssue: dependance on external services, replication may be requiredRSS is already widely used in organisations as a way to get information from the Web, LOD provides structured data to extend IT ecosystems

152. Reusing LOD example (BBC Music Beta)

153. Semantic Enterprise 2.0 use casesElectricité De France R&D:Integration of Enterprise 2.0 components using lightweight semanticsEcospace EU project:Interoperability of collaborative work environmentsEuropean Space Agency:Integration of document repositories, databases and intranet data

154. Use case: EDF R&D

155. Use case: CWE interoperabilityprivate foldersBC semantic folderBSCW shadow folder

156. Use case: European Space Agency

157. Recent developmentsFacebook Open Graph, Twitter Annotations, etc.

158. Facebook Open GraphAllows metadata from external pages to be embedded (and claimed) within Facebooke.g. metadata about a restaurant (name, location, contacts) could be imported into a Facebook news feed via a “Like” buttonGood for Facebook, good for the Semantic Web?Yes, for both!

159. A sample thing described using the OGP

160. How we could link Open Graph things to blog posts / reviews

161. OGP RDF schema (FOAF, DC, SIOC, GR)

162. Twitter AnnotationsA forthcoming initiative by Twitter whereby it will be possible to attach arbitrary metadata to any tweet:Subject to an overall limit for the metadata payloadMay be possible to attach RDF-type statementsGoing beyond annotating tweets with geotemporal information:Allowing new types and properties for tweets

163. What if your car could tweet?image from knightriderfestival.com

164. Diaspora efforthttp://nyti.ms/aDYjKQ and http://joindiaspora.com

165. OneSocialWeb

166. Appleseed project

167. 166Lots more efforts……but not joined up!Social Graph APIDiSoDataPortability

168. Everywhere real-time streamsimage from sonyericsson.com

169. Some conclusionsWe’re not there yet, but we’re getting there…

170. This area is hot right nowimage from tinyurl.com/fireflames

171. 170A vocabulary onion, building on FOAF, SKOS, SIOC, SIOC Types, DC

172. 171Disconnected sites on the Social Web / Web 2.0 can be linked using Semantic Web vocabularies

175. 174SummaryObject-centred sociality refers to how we really use social websites:Can use semantics to describe this usage, by representing objects for linkage and reuseDescribe people, networks, content, presence, knowledge, tags, etc. with semanticsInterlinking disconnected sites and profiles:Leveraging a “vocabulary onion” of ontologiesProviding solutions for novel uses in organisations:Not just for the “Social” Web, but for Enterprise 2.0

176. image from tinyurl.com/starshiptr

177. …now at Amazon.comOur new book…

178. Referenceshttp://tinyurl.com/sswrefs

179. AcknowledgementsWe thank our funding agency, Science Foundation Ireland, and also our colleagues:Uldis Bojars (SIOC)Sheila Kinsella (Semantic SNA)Milan Stankovic (OPO)