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

Copyright 2009 Digital Enterprise Research Institute. All rights reserved.

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


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

“On the Internet, nobody knows

you’re a dog.”

The New Yorker, 2005

“I had my own blog for a while,

but I decided to go back to just

pointless, incessant barking.”

11


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

12


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

13


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

http://strange.corante.com/2006/03/05/an-adoption-strategy-for-social-software-in-enterprise















http://many.corante.com/archives/2004/10/27/middlespace.php


Business metrics for Enterprise 2.0

13% of the Fortune 500 companies have a public blog

maintained by their employees

Forrester Research predicts a global market for

Enterprise 2.0 solutions of 4.6 billion dollars by 2013 and

according to Gartner , 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

21


Jive Software

22


Visible Path

Visible Path powers “Hoover‟s Connect

Lets users know how they're connected to companies and

people in the Hoover's database

23


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 !

http://retd.edf.fr


The long tail of tags


Outline







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.

http://www.w3.org/2001/sw/sweo/public/UseCases/


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 both Semantic Web 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.”

Sir Tim Berners-Lee, podcast

interview during ISWC 2005

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/

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

http://www.w3.org/2001/sw/sweo/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







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


56 of XYZ

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)

http://www.w3.org/Submission/2007/SUBM-sioc-related-20070612/


57 of XYZ

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 .


60

Argumentative discussion and SIOC


61 of XYZ

FOAF + SIOC = user and services


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

http://www.w3.org/2004/02/skos/


Finding ontologies

How to Publish Linked Data on the Web

http://www4.wiwiss.fu-berlin.de/bizer/pub/LinkedDataTutorial/

64 of XYZ





65 of XYZ

Interlinking content with SKOS


66

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


67

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



Outline

Introduction






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

http://smoc.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)

http://rdfs.org/sioc/applications/


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

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.


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/

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






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

http://www.w3.org/2005/ajar/tab

http://www4.wiwiss.fu-berlin.de/bizer/ng4j/disco/



http://sparql.captsolo.net/browser/


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

http://sioc.me


Outline

Introduction






Going further

Use cases

Conclusion


97 of XYZ

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

97 of XYZ

http://www.w3.org/2005/Incubator/rdb2rdf/RDB2RDF_SurveyReport.pdf

http://www.w3.org/2005/Incubator/rdb2rdf/RDB2RDF_SurveyReport.pdf


98 of XYZ

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

98 of XYZ

http://www.w3.org/2005/Incubator/rdb2rdf/XGR-rdb2rdf-20090126/





http://www4.wiwiss.fu-berlin.de/bizer/d2rq/




http://www.openlinksw.com/virtuoso/

http://triplify.org


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

http://linkeddata.org

http://www.ted.com/index.php/talks/tim_berners_lee_on_the_next_web.html

http://www.ted.com/index.php/talks/tim_berners_lee_on_the_next_web.html


The growing LOD cloud

100

2008

2007


The growing LOD cloud

101

2009

2008


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

http://sindice.com/

http://www.sindice.com/


Data discoverywithSindice

104 of

XYZ


Re-using LOD in IT systems

105

BBC music beta


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


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


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

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.

CWESIOC

ExporterSIOC

Importer/ViewerCWE

Third-party Application

HTTP / Web Service

CWE Data

SIOC Data



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



BSCW Shadow Folder

BC Semantic Folder

private folders



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






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

http://deri.ie

[email protected]

Alexandre Passant

http://apassant.net

UldisBojars

http://captsolo.net

John Breslin

http://johnbreslin.com

Stefan Decker

http://www.stefandecker.org

Acknowledgements

Thanks to

ourcolleaguesDeirdre Lee,

Michael Hausenblas, Giovanni

Tummarello, Mark Leyden and

Bill McDaniel for input on the

slides

Workpresentedherehas been

funded in part by Science

Foundation Ireland under

Grant No. SFI/08/CE/I1380

(Lion-2)

http://deri.ie

Technology

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