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The Social Semantic Web:ICWSM Tutorial Alexandre Passant John Breslin
Introduction Why is this important?
The Social Web is exploding! image from tinyurl.com/nuketest
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
Sites go up... image from tinyurl.com/rocket15
Facebook and Twitter
...and sites come down image from tinyurl.com/elhell
Bebo
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
It’s the social objects we create… Discussions Bookmarks Annotations Profiles Microblogs Multimedia
…that connect usto other people
Boom!
image from tinyurl.com/orionw The amount of stuff out there is vast
Social websites are like data silos image from pidgintech.com
Many isolated communities of users and their data image from pidgintech.com
Need ways to connect these islands image from pidgintech.com
Allowing users to easily move from one to another image from pidgintech.com
Enabling users to easily bring their data with them image from pidgintech.com
Semantics
The Semantic Web A brief overview
What’s in a page ? And in a link ? ? ? ?
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.
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
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.”
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.
image from www.w3.org/2007/03/layerCake.png The Semantic Web stack
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
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> .
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> .
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.
RDFa example
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
Ontologies consist mainly of classes and properties :Person a rdfs:Class . :father a rdfs:Property . :father rdfs:domain :Person . :father rdfs:range :Person .
Metadata and ontologies
Notable ontologies Social networks and social data:  FOAF, SIOC Software development:  DOAP, BEATLE Comprehensive / top-level:  Yago, OpenCYC Taxonomies and controlled vocabularies:  SKOS
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
The LOD cloud 2007 2008
The LOD cloud 2008 2009
image from richard.cyganiak.de/2007/10/lod/lod-datasets_2009-07-14.png
Representation models for the Social Semantic Web Using ontologies to model social data
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
The Social Semantic Web
FOAF Friend Of A Friend
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
FOAF (Friend-of-a-Friend)
FOAF (Friend-of-a-Friend)
FOAF at a glance
FOAF from Flickr
FOAF from Twitter
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.)
Distributed identity with FOAF
Interlinking identities and networks
Cross-site social recommendations with FOAF
Distributed authentication with FOAF+SSL
SIOC Semantically-Interlinked Online Communities
SIOC, pronounced shock image from tinyurl.com/siocshock
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 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
Some of the SIOC core ontology classes and properties
64
Designed to fit with other ontologies
Combining SIOC and FOAF
68 From last October
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
Semantic search
71
72 Find out more about the SIOC project
Semantic presence Modeling presence and status updates using semantics
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
Online PresenceOntology @@ TODO
The OPO model
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
@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 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/> . }
Semantic tagging Bridging the gap between folksonomies and ontologies
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”
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
The long tail of tags
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
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”
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
MOAT with DBpedia example data
Tagging process with MOAT and DBpedia
MOAT in Drupal
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)
Life cycle for CommonTag data
NiceTag NiceTag Ontology: Tagging meets speech act theory Focus on the link between a tag and a tagged item
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
Mining hierarchical relationships from co-occurrence of tags by Halpin et al.
LODr: semantic tagging for social data
Faviki: bookmarking meets DBpedia
Unifying conversations Some more semantically-enhanced systems
Linking IRC to the Web of Data
Mailing lists
102 Bulletin boards
SMOB
Distributedarch
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
Semantic #tagging User-driven interlinking Real-time URIs are suggested when writing content Added ability to add new webservices (e.g. enterprise microblogging)
Semantic microblogging mashups
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 <$johns_URI> . }
SPARQLing Social Semantic Web data (2) Find all users that posted replies to John’s blog since January 2008, introducing the FILTER clause: SELECT ?who WHERE {   ?post rdf:type sioct:BlogPost ; dc:title ?title ;     sioc:has_creator <$johns_URI> .   ?post sioc:has_reply ?reply .   ?reply sioc:has_creator ?who ;     dcterms:created ?date .   FILTER (?date > "2008-01-01T00:00:00Z"^^xsd:dateTime) }
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 . }
Parse SPARQL results SPARQL XML JSON: Easiest Many extensions (e.g. PHP5) Many examples
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']
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
From data to knowledge Semantic wikis
Issues with traditional wikis Structured access Information reuse Made for humans, not machines JohnGrisham He is the author of PelicanBrief.He lives in Mississippi. He writes a book each year. He is published by RandomHouse. Structured access: ,[object Object]
All authors that live in Europe? (query)Information reuse: ,[object Object]
And what if I don't speak English? (translation),[object Object]
From wikis to semantic wikis
Structure / content
SemperWiki
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
Input using Semantic MediaWiki
One possible output from a SMW query
IkeWiki
UfoWiki
FromWikipedia…
…to DBpedia @@ TODO
DBpedia mobile
Semantic social networks Using semantics in the analysis of social networks and social websites
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
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
From raw data to rich data
Some of the main sources of structured data
New possibilities for SNA and SMA
Semantic Enterprise 2.0 Enterprise 2.0 goes semantic
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)
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
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.
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
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.
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
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.
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.
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
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
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.
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
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
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
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
Reusing LOD example (BBC Music Beta)
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
Use case: EDF R&D
Use case: CWE interoperability private folders BC semantic folder BSCW shadow folder
Use case: European Space Agency
Recent developments Facebook Open Graph, Twitter Annotations, etc.
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!
A sample thing described using the OGP
How we could link Open Graph things to blog posts / reviews
OGP RDF schema (FOAF, DC, SIOC, GR)
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
What if your car could tweet? image from knightriderfestival.com
Diaspora effort http://nyti.ms/aDYjKQ and http://joindiaspora.com
OneSocialWeb
Appleseed project
166 Lots more efforts……but not joined up! Social Graph API DiSo DataPortability
Everywhere real-time streams image from sonyericsson.com
Some conclusions We’re not there yet, but we’re getting there…
This area is hot right now image from tinyurl.com/fireflames
170 A vocabulary onion, building on FOAF, SKOS, SIOC, SIOC Types, DC
171 Disconnected sites on the Social Web / Web 2.0 can be linked using Semantic Web vocabularies
174 Summary Object-centred sociality refers to how we really use social websites: Can use semantics to describe this usage, by representing objects for linkage and reuse ,[object Object],Interlinking disconnected sites and profiles: Leveraging a “vocabulary onion” of ontologies Providing solutions for novel uses in organisations: Not just for the “Social” Web, but for Enterprise 2.0
image from tinyurl.com/starshiptr
…now at Amazon.com Our new book…
References http://tinyurl.com/sswrefs

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The Social Semantic Web

  • 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
  • 7. ...and sites come down image from tinyurl.com/elhell
  • 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
  • 20.
  • 21.
  • 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.
  • 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.
  • 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 .
  • 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
  • 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
  • 45. FOAF Friend Of A Friend
  • 46.
  • 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
  • 50. FOAF at a glance
  • 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.)
  • 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
  • 62.
  • 63. Some of the SIOC core ontology classes and properties
  • 64. 64
  • 65. Designed to fit with other ontologies
  • 67.
  • 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
  • 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
  • 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
  • 84.
  • 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
  • 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
  • 95.
  • 96. Mining hierarchical relationships from co-occurrence of tags by Halpin et al.
  • 97. LODr: semantic tagging for social data
  • 99. Unifying conversations Some more semantically-enhanced systems
  • 100. Linking IRC to the Web of Data
  • 103. SMOB
  • 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)
  • 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
  • 115.
  • 116.
  • 117.
  • 118. From wikis to semantic wikis
  • 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
  • 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
  • 133.
  • 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
  • 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
  • 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
  • 173.
  • 174.
  • 175.
  • 177. …now at Amazon.com Our new book…
  • 179. Acknowledgements We thank our funding agency, Science Foundation Ireland, and also our colleagues: Uldis Bojars (SIOC) Sheila Kinsella (Semantic SNA) Milan Stankovic (OPO)

Editor's Notes

  1. FIX THE TRIPLES
  2. Alex
  3. Alex
  4. CHANGED