Semantic Enterprise 2.0 - Enabling Semantic Web technologies in Enterprise 2.0 environment

Digital Enterprise Research Institute www.deri.ie

Semantic Enterprise 2.0
EnablingSemantic Web technologies
in Enterprise 2.0 environment
Alexandre Passant, UldisBojars, John Breslin, Stefan Decker
Digital Enterprise Research Institute, National University of Ireland, Galway

Semantic Technologies Conference
15th June 2009
San José, USA
Copyright 2009 Digital Enterprise Research Institute. All rights reserved.

Outline

 Introductions and tutorial goals
 Overview of Enterprise 2.0
 Solving Enterprise 2.0 issues with Semantics
 Data models for Semantic Enterprise 2.0
 Creating RDF data in Semantic Enterprise 2.0
 Consuming Semantic Enterprise 2.0 data
 Going further
 Use cases
 Conclusion

Speakers introduction

 Alexandre Passant
 Postdoctoral researcher, DERI NUI Galway; PhD thesis
“Semantic Web technologies for Enterprise 2.0”
 UldisBojars
 PhD student at DERI, NUI Galway, Co-founder of the
SIOC Project
 John Breslin
 Researcher at DERI, NUI Galway, Lecturer at College of
Electronic Engineering, Co-founder of the SIOC project
 Stefan Decker
 Director at DERI, NUI Galway

Digital Enterprise Research Institute

Our lineage…

Memex (Vannevar Bush)
A memex is “a device in which an individual
stores all his books, records, and
communications.”
Augmenting Human Intellect
(Doug Engelbart)
“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.”
WWW (Tim Berners-Lee)
“There was a second part of the dream […] we
could then use computers to help us analyse it,
make sense of what we re doing, where we
individually fit in, and how we can better work
together.”

A Network of Knowledge

 Interconnected
 Universal
 All encompassing

 Enable global and local
collaboration
 The right information for
the right people at the right
time

Our Hypothesis…

Collaborative access to networked knowledge assists
humans, organisations and systems with their individual
as well as collective problem solving, creating solutions
to problems that were previously thought insolvable, and
enabling innovation and increased productivity on
individual, organisational and global levels.

Inspired by Doug Engelbart’s original
1962 report of: AUGMENTING
HUMAN INTELLECT: A
CONCEPTUAL FRAMEWORK

Tutorial goals

 What is Enterprise 2.0
 Identify the shortcomings of current Enterprise 2.0
ecosystems
 Explain how the Semantic Web can help to solve these
issues
 Provide technical overview on how to implement a
Semantic Web architecture for Enterprise 2.0
 Detail how to create, reuse, consume and mash-up RDF
data from several Enterprise 2.0 services
 Discuss use-cases of such approaches

Whatthis tutorial will not cover

 Business process management and relationships with
Semantic Web technologies
 Cloud computing, large-scale data management and the
Semantic Web
 Natural Language Processing techniques to mine RDF
data from non-structured content

 Talk to us if interested in this

Outline

 Introduction and tutorial goals
 Overview and shortcomings of Enterprise 2.0
 Going further
 Use cases
 Conclusion

From the Web to a “Social Web”

The New Yorker, 1993 The New Yorker, 2005

“On the Internet, nobody knows “I had my own blog for a while,
you’re a dog.” but I decided to go back to just
pointless, incessant barking.”

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Features of Web 2.0 (O’Reilly)

1. The Web as platform
2. Harnessing collective intelligence
3. Data is the next “Intel Inside”
4. End of the software release cycle
5. Lightweight programming models
6. Software above the level of a single device
7. Rich user experiences
+ The long tail

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Web 2.0 in simple terms

1. Users
2. Content
3. Tags
4. Comments
 Users post content
 Users share content
 Users annotate content with tags
 Users browse content via tags
 Users discuss content via comments
 Users connect via posted content
 Users connect directly to users

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Serious Applications for Web 2.0

 Web 2.0 in researchenvironments
 UsingWikis for projectproposals
 Scientificblogging for communities (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
 Corporate wikis
 Social Networking inside organisations
 etc.

 “Enterprise 2.0 is the use of emergent social software
platforms within companies, or between companies
and their partners or customers”
 Harvard Business School‟s Professor Andrew McAfee

Enterprise 2.0 and the Web

 Many enterprises got an online presence on Web 2.0
services to reach their customers
 Twitter, Slideshare, Flickr, etc.

The SLATES acronym

 Andrew McAfee introduced the SLATES acronym to
identify the main features of Enterprise 2.0 systems
 Search
– Information must be easily accessible for knowledge workers
 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

Social aspects of Enterprise 2.0

 Enterprise 2.0 introduces new paradigms in
organisations with regards to knowledge sharing and
communication patterns
 The social aspect is as important than the technical
requirements
 Enterprise 2.0 is a philosophy
 Enterprise 2.0 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 approach helps to
realize Enterprise 2.0
 Top-down: Hierarchy sets up new tools and requires various
services to use them
 Bottom-up: Users become evangelists and word-of-mouth
improves the number of new users
 “An adoption strategy for social software in enterprise”
– http://strange.corante.com/2006/03/05/an-adoption-strategy-for-
social-software-in-enterprise
 “MiddleSpace” by Ross Mayfield‟s (SocialText)
– 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 , social computing platforms would
be adopted by companies in the next 10 years
 Lots of companies and products in this space:
 Awareness, Mentor Scout, Contact Networks, Microsoft
SharePoint, IBM Lotus Connections, SelectMinds,
introNetworks, Tacit, Illumio, Jive Software, Visible Path,
Leverage Software, Web Crossing, SocialText

introNetworks

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Jive Software

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Visible Path

 Visible Path powers “Hoover‟s Connect
 Lets users know how they're connected to companies and
people in the Hoover's database

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Open-source applications

 Open-source Web 2.0 applications canbeefficientlyused
in organisations to build Enterprise 2.0 ecosystems
 Blogging: WordPress, b2evolution, etc.
 Wikis: MediaWiki, MoinMoin, etc.
 RSS readers and APIs MagpieRSS, etc.
 Integrated CMS: Drupal, etc.

Information fragmentation issues

 Heterogeneity of people, services, needs and practices
 Impliesthatvarious services and tools are deployed
 E.g. someuserswillprefer a wiki, another - a CMS, etc.
 By usingvarious services (blogs, wikis, etc.) information
about a particularobject (e.g. a project) isfragmented
over the company‟s network
 Getting a global pictureisdifficult
 Applications act as independent data silos, withdifferent
APIs, different data formats, etc.
 Data integrationcanbe a costlytask

Lack of machine-readable data

 Enterprise 2.0 enables and encourages people to
providevaluable content inside organisations
 Especiallywikis, collaborative and open knowledge bases
 Yet, information iscomplex to re-
use, generallylockedinside services and for human-
consumptiononly
 Lack of (common) meta-databetween applications
 Somequeriescannotbeansweredautomatically
 « List all US-basedcompaniesinvolved in sustainableenergies »
 « Whoisworking in company X for more than 6 years »

Tagging issues

 Taggingenablesuser-generated classification of content
withevolving and user-drivenvocabularies
 Avoid to learnpre-defined taxonomies or controlledvocabularies,
simpler for end-users
 Yet, itraisesvarious issues
 Tag ambiguity
– « apple »: fruit or computer brand ?
 Tag heterogeneity
– « Semtech », « semanticconference », « semtech09 »
 Lack of organisation
– No links between the tags « SPARQL » and « RDF »

Tagging issues –Use-case

 EDF R&D – http://retd.edf.fr
 > 3 years, 12257 tags, 21614 blog posts
 54.2% of tags used only one time, 75.77% uses <= 3 times
 Lots of valuable information lost in the long tail of tags
 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
 Valuable information gets lost !

The long tail of tags

Outline

 Overview of Enterprise 2.0
 Going further
 Use cases
 Conclusion

Enterprise 2.0: Semantics can help

 By using agreed-upon semantic formats to describe
people, teams, content objects and the connections
that bind them all together, Enterprise 2.0 applications
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.)
 Hence, it can be applied to extend existing
architectures with simple and lightweight add-ons

Semantic Web in Enterprise

 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/
 25 case-studies and 12 use-cases
 NASA, Eli Lilly, Oracle, Yahoo!, Sun microsystems, etc.

The (evolving) Semantic Web cake

 http://www.w3.org/2007/03/layerCake.png

Social Semantics ?

 The Semantic Web and the Social Web are not disjoint
 But can benefit of each other: Towards a Web of social and
interoperable data
 Semantics for the Social Web
 Using RDF(S)/OWL models to represent data from online
communities
 Social interactions for the Semantic Web
 Take advantage of social interactions to provide Semantic Web
data

Synergies for Social Semantics

“I think we could have Sir Tim Berners-Lee, podcast
both Semantic Web interview during ISWC 2005
technology supporting
online communities, but
at the same time also
online communities can
support Semantic
Webdata by being the
sources of people
voluntarily connecting
things together.” http://esw.w3.org/topic/IswcPodcast

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Social Semantic Information Spaces

Semantic Enterprise 2.0 Architecture

 Lightweight add-ons to existing applications to provide
RDF data
 Exporters, wrappers, dedicated scripts …
 Takingintoaccount the social aspect (e.g. semanticwikis)
 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
 Most important, it does not require to rebuild IT
infrastructure but can be plugged on existing one !
 Inspired by Tim Berners-Lee RDF Bus

The RDF Bus approach

Example architecture

http://www.w3.org/2001/sw/sw
eo/public/UseCases/EDF/

Requirements

 How to produce RDF data
 Automatically and semi-automatically from existing applications
 How to find, re-use and define ontologies
 To model data contained in Enterprise 2.0 services
 How to build interfaces on the top of it
 Browsers, searchengines, mash-
upsthatprovideadvancedcapabilities

 We will now go in detail into these topics

Outline

 Solving Enterprise 2.0 issues with Semantics
 Going further
 Use cases
 Conclusion

Data models for Enterprise 2.0

 Twokinds of data models are required to
enableSemantic Enterprise 2.0
 Models for the structure of communities and their social
interactions
 FOAF – People, groups and enterprise social networks
 SIOC –Semantically-Interlinked Online Communities–
Interactions within the community
 Models of the content
 Domain-specific ontologies
 Taxonomies (SKOS)
 Reusingexisting public RDF data (Linking Open Data)

Ontology “Onion”

FOAF (Friend-of-a-Friend)

 FOAF is an ontology for describing people and the
relationships that exist between them
 Can be integrated with any other SW vocabularies
 Widely used on the Web:

 FOAF in Enterprise 2.0 settings
 Model individuals, teams, interests / skills, etc
 Allows one‟s identity to be modeled uniformly across various
applications
 Can be used for Expert finding

Distributedidentitywith FOAF

Social networking mining with FOAF

 Can use FOAF to describe social networks in your
enterprise in a machine-readable way
 Identify connections between people between various
applications and across departments

SIOC

 Semantically-Interlinked Online Communities
 http://sioc-project.org
 SIOC is an effort from DERI to discover how we can
create and establish ontologies on the Semantic Web
 Goal of the SIOC ontology is to address interoperability issues
on the (Social) Web, both at a Web scale and in organizations
 SIOC has been adopted in a framework of
50 applications or modules deployed
on over 400 sites
 As well as corporate use-cases, more later

Motivations for SIOC

 Disconnected social websites require semantics and
ontologies for interoperation:
 Lots of social data, inherent semantics (chicken and egg)
 Potential for high impact if widely adopted on the Web
 In parallel, lack of integration between social software
and other systems in enterprise intranets
 Information fragmentation issue, as previously detailed
 Enterprise 2.0 systems could be enhanced with semantics
 Need to understand how to socially create and establish
ontologies on the Web:
 Social engineering for ontologies, in contrast to authoritative
models
 Model, agree, deploy, get feedback, re-model, etc.

The steps involved

 Develop an ontology of terms for representing rich
information about user-created content
 Lightweight ontology, easily reusable
 Create a food chain for producing, collecting and
consuming SIOC data
 Open source applications to disseminate
 As well implementation via industry and research
projects utilizing SIOC
 An effort from both academics and industry
 A constant feedback process to ensure we follow the needs of
people using it

The SIOC ontology

 The main classes and properties are:

SIOC Specification:
http://rdfs.org/sioc/spec

The SIOC food chain

Adoption of SIOC

Using SIOC in Enterprise 2.0

 Using SIOC as an ontology to represent the activities of
Enterprise communities and their content
 Represent wikis, blogs, microblogging platform, etc. with common
semantics
 Enables interoperability between different service providers on
Enterprise 2.0 environments

 Helps to solve the information fragmentation issue
 As it eases the process of querying data from various sources
within the Enterprise
 Can be efficiently combined with other internal data (e.g.
taxonomies or knowledge bases to represent discussion topics)

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Example of Enterprise 2.0 SIOC data

 John wrote meeting minutes on his team blog, powered by
Drupal:

:mypost rdf:type sioc:Post ;
dc:title “Meeting minutes” ;
sioc:has_creator :john ;
sioc:has_container :mydrupal .

:mydrupal rdf:type sioc:Forum .

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Using the SIOC Types module

 For finer-grained content types, e.g. a wiki page:

:mypagerdf:typesioct:WikiPage;
dc:title “Understanding RDF” ;
sioc:has_creator :alex ;
sioc:has_container :mywiki.

:mywikirdf:typesioct:Wiki.

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Combining with external ontologies

 To combine SIOC and other existing items, e.g. calendar
information:

:event rdf:type ical:VEVENT;
dc:title “Next meeting on friday” ;
sioc:has_creator :uldis;
sioc:has_container :mycal.

:mycal rdf:type sioct:EventCalendar .

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Argumentative discussion and SIOC

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FOAF + SIOC = user and services

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FOAF + SIOC = Data Portability

Models to represent content

 A need for dedicatedmodels to represent content of blog
posts, wiki pages, etc.
 Taxonomies and controlledvocabularies
 Can beused to definesharetopicsacross applications
 SKOS – Simple Knowledge Organisation System
 http://www.w3.org/2004/02/skos/
 Specificdomain ontologies
 Check if existingmodelscan fit yourneeds
– Best practices documents, semanticsearchengines for ontologies
(e.g. Swoogle)
 Extend if needed, republish to get public feedback

Finding ontologies

 How to Publish Linked Data on the Web
 http://www4.wiwiss.fu-berlin.de/bizer/pub/LinkedDataTutorial/

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Interlinking content with SKOS

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Models for Semantic Tagging (1)

 Solving tagging issues thanks to semantics
 Common modeling between applications
 Linking to ontologies for further semantics
 The “Tag Ontology” by Newman from 2005
 tags:Tag rdfs:subClassOf skos:Concept
A “Tagging” class describes relationships between:
– A user
– An annotated resource
– Some tags

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Models for Semantic Tagging (2)

 SCOT (Social Semantic Cloud of Tags):
 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 (Meaning of a Tag)
 A model to define “meanings” of tags using existing URIs
 e.g. SPARQL →http://dbpedia.org/resource/SPARQL
 Tagged content enters the “Linked Data” web
 Collaborative approach to share meanings in a community
– Servers can be installed in different departments / units

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Outline

 Introduction
 Data models for Semantic Enterprise 2.0
 Going further
 Use cases
 Conclusion

Getting RDF data

 Data about the services, their structure and the people
 Can be completely automated thanks to RDF exporters for
FOAF and SIOC data
 Data about the content, i.e. knowledge contained in
wikis, blogs, etc.
 Generally requires end-user input
 Semantic Wikis
 NLP techniques can be considered

Generating SIOC data

 Exporters for major open-source applications
 Drupal, WordPress, phpBB, b2evolution
 To be included in Drupal7 core w/ RDFa !
 Exporters for semi-structured data
 IRC logs, .mbox files (SWAML project)
 APIs to create your own exporters
 Native applications exporting SIOC data
 E.g. SMOB: Distributed and open semantic microblogging
 http://smob.sioc-project.org

SIOC export APIs

 Benefits
 Hides the complexity from application developers
 Can be used by people who are not Semantic Web experts
 Automatically updated according to changes in the SIOC
ontology and best practices documents
 Existing SIOC APIs:
 Java
 Perl (new!)
 PHP (most used)
 RDFa on Rails
 See http://rdfs.org/sioc/applications/ (sec 2.1)

Overview of existing SIOC exporters

 There is a large amount of structured related
information contained within message boards, and this
can be leveraged in interesting ways by exposing the
semantic data for new applications
 Exporters have been developed for commercial
(vBulletin) and open-source (phpBB) message board
systems, bringing these islands together and allowing
conversations on topics that are taking place across
various sites in a company
 Based on the SIOC PHP API

vBulletin SIOC exporter

Issues withtraditionalwikis

 Structured access JohnGrisham
 Information reuse He is the author of PelicanBrief.
 Made for humans, He lives in Mississippi.
not machines He writes a book each year.
He is published by RandomHouse.

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)

Semanticwikis

 Capture or identify further information about the pages in
a formal language, so that machines can (at least
partially) process and reason on it
 Some systems focus on metadata about the content, some on
the social aspect, some on both
 A semantic wiki could be able to capture that an article about
SPARQL related to Semantic Web and present you with further
related information
 Various use-cases and prototypes
 Some are used for personal knowledge management, others
aimed at KM for communities
 http://www.semwiki.org/

Fromwikis to Semanticwikis

Structure and content

SemPerWiki

SemanticMediaWiki

 An extension of MediaWiki:
 Allows users to add structured data to the entries, turning it into a
semantic wiki
 Users can classify the “type” of 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"
 On the page about Berlin, users can explicitly define its
population by writing:
– ... the population is [[population:=3,993,933]] ... resulting in the
semantic statement "Berlin" "has population" "3993933"
 Currently the most widely-deployed semantic wiki, Semantic
MediaWiki is also being used by various organisations, and is
being deployed as a service by Centiare and Wikia

SemanticMediaWiki

IkeWiki

UfoWiki

Outline

 Introduction
 Creating RDF data in Semantic Enterprise 2.0
 Going further
 Use cases
 Conclusion

Browsing interfaces

 Generic RDF / Linked Data browsers canbeused
 Tabulator - http://www.w3.org/2005/ajar/tab
 Disco - http://www4.wiwiss.fu-berlin.de/bizer/ng4j/disco/
 SIOC/RDF browser - http://sparql.captsolo.net/browser/
 etc.
 Provides a uniformview for content
thatwasoriginallydesignedusingdifferent applications
 Ensurehomogeneity of interfaces within a distributed information
system in Enterprise 2.0


 sparql.captsolo.net/browser

Data integration and services

 Distributed querying
 Important to keep intact the decentralized architecture of the
ecosystem
 Still experimental, can be quite slow
 Central RDF storage
 Ensure better performances
 Using SPARQL to query data and to provide HTTP-based
interface on the top of the RDF store
– SPARQL is a W3C recommendations, current SPARQL WG
discusses evolution of the language
 Lots of solutions on the market
 OpenLink Virtuoso, Sesame, etc.

Data integration and services


 Facet can be a direct or
indirect property:
Direct
 The topic of the content item
 The creator of the item
 The date created
…
Indirect
 A geographic location of the
person who created it
 The gender of the person
 An interest shared by many
creators

Social SIOC Explorer

The Sindice SIOC widget

Example of advanced applications

 The SIOC data competition
 10 Years of SIOC data fromboards.ie made to public
 http://sioc.me

 Wewillalsocoversemanticmash-ups and other interfaces
in the Use-cases section

Outline

 Introduction
 Consuming Semantic Enterprise 2.0 data
 Going further
 Use cases
 Conclusion

Relational DB to RDF Mapping

 Relational data (RDB) is structured data and can be
mapped to RDF straight-forward
 Allows integration of existing enterprise databases into the
Semantic Enterprise 2.0 architecture
 Main issues
 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

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Relational DB to RDF Mapping

 Standardization
 W3C RDB2RDF Incubator Group 2008/2009
– http://www.w3.org/2005/Incubator/rdb2rdf/XGR-rdb2rdf-20090126/
 Upcoming W3C RDB2RDF Working Group
 Current solutions (see state-of-the-art)
 D2RQ
– http://www4.wiwiss.fu-berlin.de/bizer/d2rq/
 OpenLink‟s Virtuoso
– http://www.openlinksw.com/virtuoso/
 Triplify
– http://triplify.org

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Linking Open Data

 Lost of data available on the Web in data silos
 Convertit in RDF, and interlink to enable network effect !
 Linking Open Data
 Communityprojectstarted in 2007 - http://linkeddata.org
 Billion of triples nowavailable for free
 Dbpedia, Geonames, riese (EuroStat in RDF)
 BBC, Freebase, etc.
 Raw Data Now !
 SeeTimBL‟s TED talk
 http://www.ted.com/index.php/talks/tim_berners_lee_on_the_nex
t_web.html

The growing LOD cloud

2007

2008

100

The growing LOD cloud

2008

2009

101

LOD and Semantic Enterprise 2.0

 Hugepotential for internal IT infrastructures to
enhanceexisting applications
 Integration of open and structured data fromvarious sources
atminorcost
 E.g. mashups (more later), extendeduser-interfaces, etc.
 Issue: dependance on external services
 Replicationmayberequired
 RSS isalreadywidelyused in organisations as a way to
getinformation from the Web, LOD providesstructured
data to extend IT ecosystems

Data discoverywithSindice

 Sindice Search Engine
 http://sindice.com
 Look up by RDF by keywords and on property/value
descriptions
 Simple queries but executed fast
 Discover structured data on the Web to feed your IT system
 Fast indexing (20 to 60m) of newly “pinged” information
 Sindice can be thought as a “Spider In the middle” for application
2 application semantic communication via published data

103 of
XYZ

Data discoverywithSindice

104 of
XYZ

Re-using LOD in IT systems

BBC music beta

105

Outline

 Introduction
 Going further
 Use cases
 Conclusion

Semantic Enterprise 2.0 Use cases

 Based on our own experience and projects during the
past few years
 DERI Pergamon
 Integrated framework for Enterprise 2.0
 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

Pergamon

 Integrated framework for Enterprise 2.0
 Blogs, wikis, microblogging ..
 Named entity extraction and automatic tagging
 User-profile consolidation
 Visual interfaces to browse tag / people relationships
 Based on FOAF and SIOC subsets
 To model user-profile
 Common models for different services

Pergamon

Use-case: EDF R&D

 EDF R&D: Blogs, wikis, RSS feeds
 Extensions for data integration, enabling semantic mash-ups and
semantic search
 Common semantics for various applications
 SIOC and related vocabularies
 Semantic wikis to maintain internal knowledge bases
 Lightweight ontologies (SKOS, FOAF extensions …)
 Tagging issues
 Semantic tagging with MOAT
 Features
 Search engine, semantic mash-ups, faceted browsing

Use-case: EDF R&D

 SIOC exports for common semantics between
applications (blogs, wikis, RSS feeds)
 Completely automated, full-transparency for end-user

Use-case: EDF R&D

Use-case: EDF R&D

 UfoWiki
 Specific wiki system including forms mapped to ontologies for
collaborative knowledge management
 Live SPARQL-completion to ensure homogeneity of data

Use-case: EDF R&D

 MOAT - Meaning Of A Tag
 Specific MOAT client to create new mappings with tags and
instances from the internal knowledge base
 Ability to create new instances via the same interface
 User-interface for validation / disambiguation (if needed)

Use-case: EDF R&D

 Semantic search with end-user interface
 RDF data stored in a central triple-store
 Semantic search plugged on the top of it
 Retrieving information from the different services

Use-case: EDF R&D

 Re-using RDF data from the LOD cloud internally
 Mash-ups combining internal and external data
 E.g. geolocation of wiki instances + faceted browsing

Use-case: CWE Interoperability

HTTP / Web Service

SIOC SIOC
CWE CWE
Exporter Importer/Viewer

CWE Data Third-party
Application
SIOC Data

The CWE Interoperability Architecture provides a middleware that enables
multiple, independent CWE platforms and third-party applications to share
and correlate data, based on SIOC.


1. Concept Mapping: The first stage of translating proprietary CWE data into
SIOC RDF data involves mapping concepts that exist in a specific CWE
domain to concepts in the SIOC ontology.

2. SIOC Exporter: Based on the conceptual mappings, SIOC exporters translate
platform-specific data into SIOC RDF data.

3. Basic Collaborative Services (BCS): The BCS expose the content of a CWE
workspace as SIOC data to external systems. CWE items, such as documents
and folders, may be accessed, added, deleted, renamed, or replaced remotely
via these services.

4. SIOC Importer/Viewer: Importing remote SIOC data into a CWE allows a user
to view data from a remote SIOC RDF source as if it was a local folder in the
CWE. The SIOC Importer/Viewer reverts the SIOC data into CWE platform-
specific data, based on the conceptual mappings.


 Workspace Synchronisation
 Sharing CWE files/folders between independent legacy CWE
platforms, e.g. BSCW, BC, SAP NetWeaver

 SIOC Xplore Widget
 Browsing across multiple, independent CWE platforms using a
single interface.

121 of
XYZ


private folders
BC Semantic Folder

BSCW
Shadow
Folder


123 of
XYZ

Use-case: EuropeanSpaceAgency

 Integration of Web 2.0 component withotherlegacy data
 Translating intranet HTML into RDF
 Integratingdatabaseswith D2RQ
 Extractingmetadatafrom document repositorieswith Aperture
framework + RDF transformations
 Storage and services
 SIREn (engine behind Sindice, powered by SOLr / Lucene)
 Triplestores for ranking / linkcounting
 Features
 Search engine with faceted browsing capabilities

Use-case: EuropeanSpaceAgency

Outline

 Introduction
 Going further
 Use cases
 Conclusion

Conclusion

 Enterprise 2.0 provides new communication means for
organisations, bothinternally and on the Web
 Weblogs, wikis, microblogging, RSS feeds, etc.
 Yet, itraisesvarious issues in terms of efficienlyusingthis
content
 Lack of machine-readable data, information fragmentation,
tagging issues, etc.
 Semanticscan help
 Especiallylightweightsemantics
 Can beapplied on the top of existing architectures
 Provides new features for existing applications, and a potential
for new value-added applications

Semantics for Enterprise 2.0

Outline

 Introduction
 Going further
 Use cases
 Conclusion

Thankyou !

 Contact us  Acknowledgements
 http://deri.ie  Thanks to
 firstname.lastname@deri.org ourcolleaguesDeirdre Lee,
Michael Hausenblas, Giovanni
 Alexandre Passant Tummarello, Mark Leyden and
 http://apassant.net Bill McDaniel for input on the
slides
 UldisBojars
 Workpresentedherehas been
 http://captsolo.net
funded in part by Science
 John Breslin Foundation Ireland under
 http://johnbreslin.com Grant No. SFI/08/CE/I1380
(Lion-2)
 Stefan Decker
 http://www.stefandecker.org

Semantic Enterprise 2.0 - Enabling Semantic Web technologies in Enterprise 2.0 environment

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