the social semantic web

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.” – Jyri Engestrom– 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

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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

2008

2007

The LOD cloud

2009

2008

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

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

Designed to fit with other ontologies

Combining SIOC and FOAF

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

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 Presence Ontology

• @@ 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:type foaf:Agent;foaf:mbox <mailto:fred@gmail.com>.:myCustomMessage rdf:type sioc:Post;sioc:content "anybody in for a drink tonight?".:MyCurrentPresence rdf:type opo: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:type foaf:Agent;foaf:mbox <mailto:fred@gmail.com>.:myCustomMessage rdf:type sioc:Post;sioc:content "anybody in for a drink tonight?".:MyCurrentPresence rdf:type opo: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:type opo: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

Bulletin boards

SMOB

Distributed arch

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 . ?x sioc:has_creator ?y }

WHERE { ?x a myont:BlogElement . ?x myont:created_by ?y }

From data to knowledge

Semantic wikis

Issues with traditional wikis

• Structured access• Information reuse• Made for humans, not

machines

Structured access:✗ Other books by JohnGrisham (navigation)

✗ All authors that live in Europe? (query)Information reuse:

✗ The authors from RandomHouse (views)✗ And what if I don't speak English? (translation)

JohnGrisham

He is the author of PelicanBrief.He lives in Mississippi.

He writes a book each year.He is published by RandomHouse.

Semantic wikis

• Capture 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 both

– A semantic wiki should be able to capture that an article about SPARQL is related to the Semantic Web and present you with further related information

• Various use cases and prototypes:

– http://www.semwiki.org/

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

From Wikipedia…

…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-strate

gy-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

BSCW shadow

folder

BC semantic folder

private folders

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

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

A vocabulary onion, building on FOAF, SKOS, SIOC, SIOC Types, DC

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

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• Describe people, networks, content, presence,

knowledge, tags, etc. with semantics• 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

Acknowledgements

• We thank our funding agency, Science Foundation Ireland, and also our colleagues:

– Uldis Bojars (SIOC)

– Sheila Kinsella (Semantic SNA)

– Milan Stankovic (OPO)