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Semantic Enterprise 2.0 - Enabling Semantic Web technologies in Enterprise 2.0 environment
1. 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.
2. Outline
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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
3. Speakers introduction
Digital Enterprise Research Institute www.deri.ie
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
5. Our lineage…
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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.”
6. A Network of Knowledge
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Interconnected
Universal
All encompassing
Enable global and local
collaboration
The right information for
the right people at the right
time
7. Our Hypothesis…
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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
8. Tutorial goals
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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
9. Whatthis tutorial will not cover
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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
10. Outline
Digital Enterprise Research Institute www.deri.ie
Introduction and tutorial goals
Overview and shortcomings 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
11. From the Web to a “Social Web”
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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.”
11
12. Features of Web 2.0 (O’Reilly)
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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
12
13. Web 2.0 in simple terms
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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
13
14. Serious Applications for Web 2.0
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Web 2.0 in researchenvironments
UsingWikis for projectproposals
Scientificblogging for communities (e.g. Nature network)
15. Enterprise 2.0
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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
16. Enterprise 2.0 and the Web
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Many enterprises got an online presence on Web 2.0
services to reach their customers
Twitter, Slideshare, Flickr, etc.
17. The SLATES acronym
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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
18. Social aspects of Enterprise 2.0
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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.
19. Keys to Enterprise 2.0 adoption
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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
20. Business metrics for Enterprise 2.0
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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
23. Visible Path
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Visible Path powers “Hoover‟s Connect
Lets users know how they're connected to companies and
people in the Hoover's database
23
24. Open-source applications
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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.
25. Information fragmentation issues
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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
26. Lack of machine-readable data
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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 »
27. Tagging issues
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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 »
28. Tagging issues –Use-case
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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 !
29. The long tail of tags
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30. Outline
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Introduction 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
31. Enterprise 2.0: Semantics can help
Digital Enterprise Research Institute www.deri.ie
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
32. Semantic Web in Enterprise
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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.
33. The (evolving) Semantic Web cake
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http://www.w3.org/2007/03/layerCake.png
34. Social Semantics ?
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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
35. Synergies for Social Semantics
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“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
35 of XYZ
37. Semantic Enterprise 2.0 Architecture
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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
38. The RDF Bus approach
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40. Requirements
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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
41. Outline
Digital Enterprise Research Institute www.deri.ie
Introduction 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
42. Data models for Enterprise 2.0
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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)
44. FOAF (Friend-of-a-Friend)
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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
46. Social networking mining with FOAF
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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
47. SIOC
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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
48. Motivations for SIOC
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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.
51. The steps involved
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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
52. The SIOC ontology
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The main classes and properties are:
SIOC Specification:
http://rdfs.org/sioc/spec
53. The SIOC food chain
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56. Using SIOC in Enterprise 2.0
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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)
56 of XYZ
57. Example of Enterprise 2.0 SIOC data
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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 .
57 of XYZ
58. Using the SIOC Types module
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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.
58 of XYZ
59. Combining with external ontologies
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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 .
59 of XYZ
61. FOAF + SIOC = user and services
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61 of XYZ
62. FOAF + SIOC = Data Portability
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63. Models to represent content
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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
64. Finding ontologies
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How to Publish Linked Data on the Web
http://www4.wiwiss.fu-berlin.de/bizer/pub/LinkedDataTutorial/
64 of XYZ
66. Models for Semantic Tagging (1)
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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
66
67. Models for Semantic Tagging (2)
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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
67
69. Outline
Digital Enterprise Research Institute www.deri.ie
Introduction
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
70. Getting RDF data
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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
71. Generating SIOC data
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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
72. SIOC export APIs
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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)
73. Overview of existing SIOC exporters
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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
76. Issues withtraditionalwikis
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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)
77. Semanticwikis
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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/
81. SemanticMediaWiki
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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
85. Outline
Digital Enterprise Research Institute www.deri.ie
Introduction
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
86. Browsing interfaces
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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
88. Data integration and services
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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.
92. Digital Enterprise Research Institute www.deri.ie
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
94. The Sindice SIOC widget
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95. Example of advanced applications
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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
96. Outline
Digital Enterprise Research Institute www.deri.ie
Introduction
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
97. Relational DB to RDF Mapping
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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
97 of XYZ 97 of XYZ
98. Relational DB to RDF Mapping
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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
98 of XYZ 98 of XYZ
99. Linking Open Data
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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
100. The growing LOD cloud
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2007
2008
100
101. The growing LOD cloud
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2008
2009
101
102. LOD and Semantic Enterprise 2.0
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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
103. Data discoverywithSindice
Digital Enterprise Research Institute www.deri.ie
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
105. Re-using LOD in IT systems
Digital Enterprise Research Institute www.deri.ie
BBC music beta
105
106. Outline
Digital Enterprise Research Institute www.deri.ie
Introduction
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
107. Semantic Enterprise 2.0 Use cases
Digital Enterprise Research Institute www.deri.ie
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
108. Pergamon
Digital Enterprise Research Institute www.deri.ie
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
111. Use-case: EDF R&D
Digital Enterprise Research Institute www.deri.ie
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
112. Use-case: EDF R&D
Digital Enterprise Research Institute www.deri.ie
SIOC exports for common semantics between
applications (blogs, wikis, RSS feeds)
Completely automated, full-transparency for end-user
114. Use-case: EDF R&D
Digital Enterprise Research Institute www.deri.ie
UfoWiki
Specific wiki system including forms mapped to ontologies for
collaborative knowledge management
Live SPARQL-completion to ensure homogeneity of data
116. Use-case: EDF R&D
Digital Enterprise Research Institute www.deri.ie
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)
117. Use-case: EDF R&D
Digital Enterprise Research Institute www.deri.ie
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
118. Use-case: EDF R&D
Digital Enterprise Research Institute www.deri.ie
Re-using RDF data from the LOD cloud internally
Mash-ups combining internal and external data
E.g. geolocation of wiki instances + faceted browsing
119. Use-case: CWE Interoperability
Digital Enterprise Research Institute www.deri.ie
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.
120. Use-case: CWE Interoperability
Digital Enterprise Research Institute www.deri.ie
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.
121. Use-case: CWE Interoperability
Digital Enterprise Research Institute www.deri.ie
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
124. Use-case: EuropeanSpaceAgency
Digital Enterprise Research Institute www.deri.ie
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
127. Outline
Digital Enterprise Research Institute www.deri.ie
Introduction
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
128. Conclusion
Digital Enterprise Research Institute www.deri.ie
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
130. Outline
Digital Enterprise Research Institute www.deri.ie
Introduction
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
131. Thankyou !
Digital Enterprise Research Institute www.deri.ie
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