ICWSM Tutorial / Washington, DC, USA / 23rd May 2010

1. The Social Semantic Web:ICWSM Tutorial Alexandre Passant John Breslin

2. Introduction Why is this important?

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

4. 61% = social networks 11% = forums 11% = UG content sites, e.g. urbandictionary.com 10% = UG marketplaces, e.g. craigslist.org 03% = blogs 01% = UG reviews, e.g. apartmentratings.com 01% = wikis 02% = other text from tinyurl.com/briscougc

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

6. Facebook and Twitter

7. ...and sites come down image from tinyurl.com/elhell

8. Bebo

9. Object-centred sociality (AKA social objects) gives some explanations 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 del.icio.us = bookmarks Blogs = discussion posts

10. It’s the social objects we create… Discussions Bookmarks Annotations Profiles Microblogs Multimedia

11. …that connect usto other people

12. Boom!

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

14. Social websites are like data silos image from pidgintech.com

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

16. Need ways to connect these islands image from pidgintech.com

17. Allowing users to easily move from one to another image from pidgintech.com

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

19. Semantics

22. The Semantic Web A 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 Web Bridging the gap between a Web of Documents to a Web of Data, with typed objects and typed relationships Adding machine-readable metadata to existing content, so that information can be parsed, queried, reused Defining shared semantics for this metadata to allow interoperability between applications and for advanced purposes, such as reasoning Enabling machine-readable knowledge at Web scale, making information more easy to find and process

26. A bit of history Memex, 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 2010 Most 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.png The Semantic Web stack

29. 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. http://dbpedia.org/resource/Galway

30. 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> .

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. RDFa A way of embedding RDF in (X)HTML documents: One page for both humans and machines Don’t need to repeat yourself Introducing new XHTML attributes Current work is ongoing on RDFa 1.1: For profiles, etc.

33. RDFa example

34. 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 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 ontologies Social networks and social data: FOAF, SIOC Software development: DOAP, BEATLE Comprehensive / top-level: Yago, OpenCYC Taxonomies and controlled vocabularies: SKOS

38. 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: 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 cloud 2007 2008

40. The LOD cloud 2008 2009

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

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

43. Semantics can help social websites, and vice versa By 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 semantics Developers 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. FOAF Friend 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 networks Can be integrated with other SW vocabularies FOAF 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 data Facebook: http://www.dcs.shef.ac.uk/~mrowe/foafgenerator.html Twitter: 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. SIOC Semantically-Interlinked Online Communities

59. SIOC, pronounced shock image 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 Web Goal of the SIOC ontology is to address interoperability issues on the (Social) Web http://sioc-project.org/ SIOC has been adopted in a framework of 50 applications or modules deployed on over 400 sites Various domains: Web 2.0, enterprise information integration, HCLS, e-government

61. 61 The aims of SIOC To “semantically-interlink online communities” To fully describe content / structure of social websites To create new connections between online discussion posts and items, forums and containers To enable the integration of online community info To browse connected Social Web items in interesting and innovative ways To 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. 68 From last October

69. SIOC and other RDFa in Drupal 7 Drupal 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. 72 Find out more about the SIOC project

73. Semantic presence Modeling presence and status updates using semantics

74. Motivations There 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 people Model 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 tagging Bridging the gap between folksonomies and ontologies

81. 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”

82. Use case illustrating such issues Corporate use case > 3 years, 12257 tags, 21614 posts: 54.2% of tags used once, 75.77% used <= 3 times Lots of valuable information lost in the long tail Tagging 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 Ontology The “Tag Ontology” by Newman from 2005: http://www.holygoat.co.uk/projects/tags/ 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

86. SCOT SCOT (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 another Share tagclouds between services, and between users “Tag portability”

87. MOAT MOAT (Meaning Of A Tag): http://moat-project.org/ A model to define “meanings” of tags e.g. SPARQL ->http://dbpedia.org/resource/SPARQL User-driven interlinking Tagged content enters the “Linked Data” web Collaborative 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. CommonTag CommonTag: http://commontag.org/ A joint effort by AdaptiveBlue, DERI at NUI Galway, Faviki, Freebase, Yahoo!, Zemanta and Zigtag Linking tags to meaningful resource (à la MOAT)

92. Life cycle for CommonTag data

93. NiceTag NiceTag Ontology: Tagging meets speech act theory Focus on the link between a tag and a tagged item

94. Extracting ontologies from tags FolksOntology: Semi-assisted extraction of relationships between tags FLOR: FoLksonomy Ontology enRichment http://flor.kmi.open.ac.uk/ Automated approach to identify tag meanings Can 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 conversations Some more semantically-enhanced systems

100. Linking IRC to the Web of Data

101. Mailing lists

102. 102 Bulletin boards

103. SMOB

104. Distributedarch

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

106. Semantic #tagging User-driven interlinking Real-time URIs are suggested when writing content Added ability to add new webservices (e.g. enterprise microblogging)

107. Semantic microblogging mashups

108. SPARQLing Social Semantic Web data Find all posts and their titles by John, using SELECT, and combining vocabularies (DC, SIOC, SIOC Types): SELECT ?post ?title WHERE { ?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 ?who WHERE { ?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 person SELECT ?item WHERE { ?person foaf:openid <$openid> ; foaf:holdsAccount ?user . ?user sioc:creator_of ?item . }

111. Parse SPARQL results SPARQL XML JSON: Easiest Many extensions (e.g. PHP5) Many examples

112. Querying RDF files Redland: http://librdf.org Bindings: 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 data Semantic Pipes: http://pipes.deri.org/ SPARQL constructs: The “XSLT” of RDF; translate a set of RDF data from one graph format to another CONSTRUCT { ?x a sioc:Post . ?xsioc:has_creator ?y } WHERE { ?x a myont:BlogElement . ?xmyont:created_by ?y } 113

114. From data to knowledge Semantic wikis

118. From wikis to semantic wikis

119. Structure / content

120. SemperWiki

121. Semantic MediaWiki An 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 networks Using semantics in the analysis of social networks and social websites

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

131. boards.ie use case 10 years of conversations, 150k users, 7M posts: Analysing the structured data that people link to To 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 2.0 Enterprise 2.0 goes semantic

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

138. 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

139. 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.

140. 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

141. 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.

142. 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: http://strange.corante.com/2006/03/05/an-adoption-strategy-for-social-software-in-enterprise http://many.corante.com/archives/2004/10/27/middlespace.php

143. 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.

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 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

146. Lack of machine-readable data and tagging issues 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

147. 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): http://www.w3.org/2001/sw/sweo/public/UseCases/ NASA, Eli Lilly, Oracle, Yahoo!, Sun, etc.

148. 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

149. 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

150. 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 http://www.w3.org/2005/Incubator/rdbrdf/RDB2RDF_SurveyReport.pdf

151. 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

152. Reusing LOD example (BBC Music Beta)

153. 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 European Space Agency: Integration of document repositories, databases and intranet data

154. Use case: EDF R&D

155. Use case: CWE interoperability private folders BC semantic folder BSCW shadow folder

156. Use case: European Space Agency

157. Recent developments Facebook Open Graph, Twitter Annotations, etc.

158. Facebook Open Graph Allows metadata from external pages to be embedded (and claimed) within Facebook e.g. metadata about a restaurant (name, location, contacts) could be imported into a Facebook news feed via a “Like” button Good 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 Annotations A forthcoming initiative by Twitter whereby it will be possible to attach arbitrary metadata to any tweet: Subject to an overall limit for the metadata payload May be possible to attach RDF-type statements Going 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 effort http://nyti.ms/aDYjKQ and http://joindiaspora.com

165. OneSocialWeb

166. Appleseed project

167. 166 Lots more efforts……but not joined up! Social Graph API DiSo DataPortability

168. Everywhere real-time streams image from sonyericsson.com

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

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

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

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

176. image from tinyurl.com/starshiptr

177. …now at Amazon.com Our new book…

178. References http://tinyurl.com/sswrefs

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