SlideShare a Scribd company logo

Linked data for Enterprise Data Integration

The Web evolves into a Web of Data. In parallel Intranets of large companies will evolve into Data Intranets based on the Linked Data principles. Linked Data has the potential to complement the SOA paradigm with a light-weight, adaptive data integration approach.

1 of 35
Download to read offline
Linked Data for Enterprise Information
Integration
Sören Auer
© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
The Web evolves into a Web of Data
2
Linked Open Data
Facebook
Open Graph
© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
The Evolution of the Web
3
Web 1.0 - Hypertext
 Static Web pages
 Hyperlinks
 Link directories
Web 2.0 – Social Apps
 Social Web
 Crowd-sourcing
 Mashups
Web 3.0 – Linked Data
 REST APIs, RDF,
JSON-LD
 Vocabularies
 Rich-snippets,
Semantic Search
1990 2000 2010
Intranet 1.0 - Hypertext
 Static Intranet pages
 Keyword search
 Hyperlinks
Intranet 2.0 –
Social Enterprise Apps
 Salesforce
 Crowd-sourcing
 Mashups
Intranet 3.0 –
Enterprise Data Intranet
 URI Scheme
 Enterprise taxonomies /
knowledge bases
 RDB2RDF Mapping
1995 2005 2015
& Enterprise Intranets
© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
Linked Data Principles
1. Use URIs to identify the “things” in your data
2. Use http:// URIs so people (and machines) can
look them up on the web
3. When a URI is looked up, return a description of
the thing (in RDF format)
4. Include links to related things
http://www.w3.org/DesignIssues/LinkedData.html
4
© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
Linked Enterprise Data Principles
1. Evolve existing existing taxonomies into enterprise knowledge bases/hubs
2. Establish a enterprise wide URI scheme
3. Equip existing information systems in your intranet with Linked Data
interfaces
4. Establish links between related information
5
© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
Linked Enterprise Data Advantages
• Light-weight linked data integration complements more
complex SOA architectures
• Unified data (access) model simplifies data integration
• Increase standardization while preserving diversity
• Facilitate information flows along supply and value
creation chains
 Dramatically reduce data integration costs, increase
enterprise flexibility
6
Creating Knowledge
out of Interlinked Data
Inter-linking/
Fusing
Classifi-cation/
Enrichment
Quality
Analysis
Evolution /
Repair
Search/
Browsing/
Exploration
Extraction
Storage/
Querying
Manual
revision/
authoring
Linked Data
Lifecycle
Creating Knowledge
out of Interlinked Data
Extraction
Inter-
linking
Enrichm
ent
Quality
Analysis
Evolution
Repair
Explora-
tion
Extrac-
tion
Store
Query
Author
ing
Creating Knowledge
out of Interlinked Data
From unstructured sources
• NLP, text mining, annotation
From semi-structured sources
• DBpedia, LinkedGeoData, DataCube
From structured sources
• RDB2RDF
Extraction
Creating Knowledge
out of Interlinked Data
Many different approaches: D2R, Virtuoso RDF Views, Triplify,
No agreement on a formal
semantics of RDF2RDF
mapping
• LOD readiness,
SPARQL-SQL translation
W3C RDB2RDF WG
Extraction Relational Data
Tool Triplify Sparqlify D2RQ
Virtuoso
RDF Views
Technology
Scripting
languages
(PHP)
Java Java
Whole
middleware
solution
SPARQL
endpoint
- X X X
Mapping
language
SQL
SPARQL
CONSTRUCT
Views + SQL
RDF based RDF based
Mapping
generation
Manual
Semi-
automatic
Semi-
automatic
Manual
Scalability
Medium-
high
(but no
SPARQL)
Very high Medium High
Malhotra, Auer, Erling, Hausenblas: W3C RDB2RDF Incubator Group Report. W3C RDB2RDF Incubator Group, 2009.
Creating Knowledge
out of Interlinked Data
• Rationale: Exploit existing formalisms
(SQL, SPARQL Construct) as much as
possible
• flexible & versatile mapping language
• translating one SPARQL query into
exactly one efficiently executable SQL
query
• Solid theoretical formalization based on
SPARQL-relational algebra
transformations
• Extremely scalable through elaborated
view candidate selection mechanism
• Used to publish 20B triples for
LinkedGeoData
Sparqlify
Stadler, Unbehauen, Auer, Lehmann: Sparqlify – Very Large Scale Linked Data Publication from Relational Databases.
Submitted to VLDB-Journal.
SPARQL
Construct
SQL
View
Bridge
Creating Knowledge
out of Interlinked Data
Storage and Querying
Inter-
linking
Enrichm
ent
Quality
Analysis
Evolution
Repair
Explora-
tion
Extrac-
tion
Store
Query
Author
ing
Authoring
Inter-
linking
Enrichm
ent
Quality
Analysis
Evolution
Repair
Explora-
tion
Extrac-
tion
tore
uery
Author
ing
Creating Knowledge
out of Interlinked Data
1. Semantic (Text) Wikis
• Authoring of semantically
annotated texts
2. Semantic Data Wikis
• Direct authoring of
structured information
(i.e. RDF, RDF-Schema,
OWL)
Two Kinds of Semantic Wikis
Creating Knowledge
out of Interlinked Data
The situation at Daimler (€97.76 billion revenue, 250.000
employees):
• 3.000 heterogeneous IT systems
• Different units (car, bus, truck etc.) with very different views
• No common language
• Inability to identify crucial entities (parts, locations etc.)
enterprise wide
There is no (can not be a) single Enterprise Information Model
A distributed, iterative, bottom-up integration approach such as
Linked Data might be able to help (pay-as-you-go).
Can Linked Data help to solve the EII
problem in a fortune-500 company?
Creating Knowledge
out of Interlinked Data
16
Search before
Creating Knowledge
out of Interlinked Data
Creating Knowledge
out of Interlinked Data
OntoWiki
with loaded
car model
data
Creating Knowledge
out of Interlinked Data
Management of Enterprise Taxonomies with OntoWiki
Based on the W3C SKOS standard
Corporate Language Management at Daimler: 500k concepts in
20 languages
Creating Knowledge
out of Interlinked Data
Search after
Showing recommondations
from the knowledge base
integrating car model data
and enterprise taxonomy
Creating Knowledge
out of Interlinked Data
You can search for „Kombi“
(station wagon) and find T-
Models (Daimler term for
station waggon)
FromIntranettoEnterpriseDataWebaroundaknowledgehub
Auer, Frischmuth, Klímek, Unbehauen, Holzweißig, Marquardt: Linked Data in Enterprise Information Integration
Submitted to Semantic Web Journal 2012.
Creating Knowledge
out of Interlinked Data
© CC-BY-NC-ND by ~Dezz~ (residae on flickr)
Linking
Inter-
linking
Enrichm
ent
Quality
Analysis
Evolution
Repair
Explora-
tion
Extrac-
tion
Store
Query
Author
ing
Creating Knowledge
out of Interlinked Data
In an uncontrolled
environment as the Data
Web, there will be a
proliferation of equivalent
or similar entity identifiers
Manual Link discovery:
• Sindice integration into UIs
• Semantic Pingback
Semi-automatic:
• SILK
• LIMES
Automatic/ Supervised:
• Raven [1]
Linking Entities on the Data Web
[1] Ngonga, Lehmann, Auer, Höffner: RAVEN -- Active Learning of Link Specifications, OM@ISWC, 2011.
Creating Knowledge
out of Interlinked Data
Enrichment
Inter-
linking
Enrichm
ent
Quality
Analysis
Evolution
Repair
Explora-
tion
Extrac-
tion
Store
Query
Author
ing
Creating Knowledge
out of Interlinked Data
Linked Data is mainly instance data!!!
ORE (Ontology Repair and Enrichment) tool allows to improve an
OWL ontology by fixing inconsistencies & making suggestions for
adding further axioms.
• Ontology Debugging: OWL reasoning to detect inconsistencies and
satisfiable classes + detect the most likely sources for the problems.
user can create a repair plan, while maintaining full control.
• Ontology Enrichment: uses the DL-Learner framework to suggest
definitions & super classes for existing classes in the KB. works if
instance data is available for harmonising schema and data.
http://aksw.org/Projects/ORE
Enrichment & Repair
Lehmann, Auer, Tramp: Class Expression Learning for Ontology Engineering. Journal of Web Semantics (JWS), 2011.
Creating Knowledge
out of Interlinked Data
Analysis
Quality
Inter-
linking
Enrichm
ent
Quality
Analysis
Evolution
Repair
Explora-
tion
Extrac-
tion
Store
Query
Author
ing
CC BY SA Wikipedia
Creating Knowledge
out of Interlinked Data
Quality on the Data Web is varying a lot
• Hand crafted or expensively curated knowledge base
(e.g. DBLP, UMLS) vs. extracted from text or Web
2.0 sources (DBpedia)
Research Challenge
• Establish measures for assessing the authority,
provenance, reliability of Data Web resources
Opportunity for EII: Employ crowd-sourced
knowledge from the Data Web in the Enterprise
Linked Data Quality Analysis
FP7-IP DIACHRON Managing the Evolution and Preservation of the Data Web
Started April 2013
Creating Knowledge
out of Interlinked Data
Evolution © CC-BY-SA by alasis on flickr)
Inter-
linking
Enrichm
ent
Quality
Analysis
Evolution
Repair
Explora-
tion
Extrac-
tion
Store
Query
Author
ing
Creating Knowledge
out of Interlinked Data
Exploration
Inter-
linking
Enrichm
ent
Quality
Analysis
Evolution
Repair
Explora-
tion
Extrac-
tion
Store
Query
Author
ing
Creating Knowledge
out of Interlinked Data
An ecosystem of LOD visualizations
LODExploration
Widgets
Spatial faceted-
browsing
Faceted-
browsing
Statistical
visualization
Entity-/faceted-
Based browsing
Domain specific
visualizations … …
LODDatasetsChoreography
layer
• Dataset analysis (size, vocabularies, property histograms etc.)
• Selection of suitable visualization widgets
Brunetti, Auer, García: The Linked Data Visualization Model. To appear in IJSWIS, 2012.
Creating Knowledge
out of Interlinked Data
LOD Life-(Washing-)cycle supported by Debian
based LOD2 Stack
http://stack.lod2.eu
Creating Knowledge
out of Interlinked Data
Linked Enterprise Intra Data Webs fill the gap
between Intra-/Extranets and EIS/ERP
Unstructured Information
Management
Structured Information
Management
Support the long tail of enterprise information domains
• Human-resources
• Requirements engineering
• Supply-chains
Creating Knowledge
out of Interlinked Data
• Linked Data is a promising technology for closing the
gap between SOA and unstructured information
management
• wealth of knowledge available as LOD can be
leveraged as background knowledge for Enterprise
applications
• The application of Linked Data in the enterprise is still
largely unexplored (opportunity)
• Linked Data will make Enterprise Information Integration
more flexible, iterative, cost effective
Take home messages
Auer, Frischmuth, Klímek, Tramp, Unbehauen, Holzweißig, Marquardt: Linked Data in Enterprise Information Integration
Submitted to Semantic Web Journal.
Creating Knowledge
out of Interlinked Data
Thanks for your attention!
Sören Auer
http://www.informatik.uni-leipzig.de/~auer | http://aksw.org | http://lod2.org
auer@cs.uni-bonn.de

Recommended

What can linked data do for digital libraries
What can linked data do for digital librariesWhat can linked data do for digital libraries
What can linked data do for digital librariesSören Auer
 
Towards digitizing scholarly communication
Towards digitizing scholarly communicationTowards digitizing scholarly communication
Towards digitizing scholarly communicationSören Auer
 
Introduction to the Data Web, DBpedia and the Life-cycle of Linked Data
Introduction to the Data Web, DBpedia and the Life-cycle of Linked DataIntroduction to the Data Web, DBpedia and the Life-cycle of Linked Data
Introduction to the Data Web, DBpedia and the Life-cycle of Linked DataSören Auer
 
Enterprise knowledge graphs
Enterprise knowledge graphsEnterprise knowledge graphs
Enterprise knowledge graphsSören Auer
 
Towards an Open Research Knowledge Graph
Towards an Open Research Knowledge GraphTowards an Open Research Knowledge Graph
Towards an Open Research Knowledge GraphSören Auer
 
LDOW2015 Position Talk and Discussion
LDOW2015 Position Talk and DiscussionLDOW2015 Position Talk and Discussion
LDOW2015 Position Talk and DiscussionSören Auer
 
Knowledge Graph Introduction
Knowledge Graph IntroductionKnowledge Graph Introduction
Knowledge Graph IntroductionSören Auer
 

More Related Content

What's hot

Das Semantische Daten Web für Unternehmen
Das Semantische Daten Web für UnternehmenDas Semantische Daten Web für Unternehmen
Das Semantische Daten Web für UnternehmenSören Auer
 
From Open Linked Data towards an Ecosystem of Interlinked Knowledge
From Open Linked Data towards an Ecosystem of Interlinked KnowledgeFrom Open Linked Data towards an Ecosystem of Interlinked Knowledge
From Open Linked Data towards an Ecosystem of Interlinked KnowledgeSören Auer
 
Creating knowledge out of interlinked data
Creating knowledge out of interlinked dataCreating knowledge out of interlinked data
Creating knowledge out of interlinked dataSören Auer
 
Describing Scholarly Contributions semantically with the Open Research Knowle...
Describing Scholarly Contributions semantically with the Open Research Knowle...Describing Scholarly Contributions semantically with the Open Research Knowle...
Describing Scholarly Contributions semantically with the Open Research Knowle...Sören Auer
 
Build Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural HeritageBuild Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural HeritageOntotext
 
Towards Knowledge Graph based Representation, Augmentation and Exploration of...
Towards Knowledge Graph based Representation, Augmentation and Exploration of...Towards Knowledge Graph based Representation, Augmentation and Exploration of...
Towards Knowledge Graph based Representation, Augmentation and Exploration of...Sören Auer
 
Getting Started with Knowledge Graphs
Getting Started with Knowledge GraphsGetting Started with Knowledge Graphs
Getting Started with Knowledge GraphsPeter Haase
 
Knowledge graphs on the Web
Knowledge graphs on the WebKnowledge graphs on the Web
Knowledge graphs on the WebArmin Haller
 
FAIR data: LOUD for all audiences
FAIR data: LOUD for all audiencesFAIR data: LOUD for all audiences
FAIR data: LOUD for all audiencesAlessandro Adamou
 
SemWeb Fundamentals - Info Linking & Layering in Practice
SemWeb Fundamentals - Info Linking & Layering in PracticeSemWeb Fundamentals - Info Linking & Layering in Practice
SemWeb Fundamentals - Info Linking & Layering in PracticeDan Brickley
 
Introduction to the Semantic Web
Introduction to the Semantic WebIntroduction to the Semantic Web
Introduction to the Semantic WebNuxeo
 
Linking Open, Big Data Using Semantic Web Technologies - An Introduction
Linking Open, Big Data Using Semantic Web Technologies - An IntroductionLinking Open, Big Data Using Semantic Web Technologies - An Introduction
Linking Open, Big Data Using Semantic Web Technologies - An IntroductionRonald Ashri
 
Linked data as a library data platform
Linked data as a library data platformLinked data as a library data platform
Linked data as a library data platformJindřich Mynarz
 
Quick Linked Data Introduction
Quick Linked Data IntroductionQuick Linked Data Introduction
Quick Linked Data IntroductionMichael Hausenblas
 
Scalable and privacy-preserving data integration - part 1
Scalable and privacy-preserving data integration - part 1Scalable and privacy-preserving data integration - part 1
Scalable and privacy-preserving data integration - part 1ErhardRahm
 
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Jeff Z. Pan
 
Keystone summer school_2015_miguel_antonio_ldcompression_4-joined
Keystone summer school_2015_miguel_antonio_ldcompression_4-joinedKeystone summer school_2015_miguel_antonio_ldcompression_4-joined
Keystone summer school_2015_miguel_antonio_ldcompression_4-joinedJoel Azzopardi
 

What's hot (20)

Das Semantische Daten Web für Unternehmen
Das Semantische Daten Web für UnternehmenDas Semantische Daten Web für Unternehmen
Das Semantische Daten Web für Unternehmen
 
From Open Linked Data towards an Ecosystem of Interlinked Knowledge
From Open Linked Data towards an Ecosystem of Interlinked KnowledgeFrom Open Linked Data towards an Ecosystem of Interlinked Knowledge
From Open Linked Data towards an Ecosystem of Interlinked Knowledge
 
Creating knowledge out of interlinked data
Creating knowledge out of interlinked dataCreating knowledge out of interlinked data
Creating knowledge out of interlinked data
 
Describing Scholarly Contributions semantically with the Open Research Knowle...
Describing Scholarly Contributions semantically with the Open Research Knowle...Describing Scholarly Contributions semantically with the Open Research Knowle...
Describing Scholarly Contributions semantically with the Open Research Knowle...
 
Build Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural HeritageBuild Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
 
Towards Knowledge Graph based Representation, Augmentation and Exploration of...
Towards Knowledge Graph based Representation, Augmentation and Exploration of...Towards Knowledge Graph based Representation, Augmentation and Exploration of...
Towards Knowledge Graph based Representation, Augmentation and Exploration of...
 
Getting Started with Knowledge Graphs
Getting Started with Knowledge GraphsGetting Started with Knowledge Graphs
Getting Started with Knowledge Graphs
 
Knowledge graphs on the Web
Knowledge graphs on the WebKnowledge graphs on the Web
Knowledge graphs on the Web
 
FAIR data: LOUD for all audiences
FAIR data: LOUD for all audiencesFAIR data: LOUD for all audiences
FAIR data: LOUD for all audiences
 
SemWeb Fundamentals - Info Linking & Layering in Practice
SemWeb Fundamentals - Info Linking & Layering in PracticeSemWeb Fundamentals - Info Linking & Layering in Practice
SemWeb Fundamentals - Info Linking & Layering in Practice
 
Introduction to the Semantic Web
Introduction to the Semantic WebIntroduction to the Semantic Web
Introduction to the Semantic Web
 
Linked library data
Linked library dataLinked library data
Linked library data
 
Linking Open, Big Data Using Semantic Web Technologies - An Introduction
Linking Open, Big Data Using Semantic Web Technologies - An IntroductionLinking Open, Big Data Using Semantic Web Technologies - An Introduction
Linking Open, Big Data Using Semantic Web Technologies - An Introduction
 
DBPedia-past-present-future
DBPedia-past-present-futureDBPedia-past-present-future
DBPedia-past-present-future
 
Linked data as a library data platform
Linked data as a library data platformLinked data as a library data platform
Linked data as a library data platform
 
Linking library data
Linking library dataLinking library data
Linking library data
 
Quick Linked Data Introduction
Quick Linked Data IntroductionQuick Linked Data Introduction
Quick Linked Data Introduction
 
Scalable and privacy-preserving data integration - part 1
Scalable and privacy-preserving data integration - part 1Scalable and privacy-preserving data integration - part 1
Scalable and privacy-preserving data integration - part 1
 
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...
 
Keystone summer school_2015_miguel_antonio_ldcompression_4-joined
Keystone summer school_2015_miguel_antonio_ldcompression_4-joinedKeystone summer school_2015_miguel_antonio_ldcompression_4-joined
Keystone summer school_2015_miguel_antonio_ldcompression_4-joined
 

Similar to Linked data for Enterprise Data Integration

Linked Data Tutorial
Linked Data TutorialLinked Data Tutorial
Linked Data TutorialSören Auer
 
PoolParty SKOS and Linked Data
PoolParty SKOS and Linked DataPoolParty SKOS and Linked Data
PoolParty SKOS and Linked DataAndreas Blumauer
 
Paul houle resume
Paul houle resumePaul houle resume
Paul houle resumePaul Houle
 
PoolParty Thesaurus Management - ISKO UK, London 2010
PoolParty Thesaurus Management - ISKO UK, London 2010PoolParty Thesaurus Management - ISKO UK, London 2010
PoolParty Thesaurus Management - ISKO UK, London 2010Andreas Blumauer
 
X api chinese cop monthly meeting feb.2016
X api chinese cop monthly meeting   feb.2016X api chinese cop monthly meeting   feb.2016
X api chinese cop monthly meeting feb.2016Jessie Chuang
 
Why I don't use Semantic Web technologies anymore, event if they still influe...
Why I don't use Semantic Web technologies anymore, event if they still influe...Why I don't use Semantic Web technologies anymore, event if they still influe...
Why I don't use Semantic Web technologies anymore, event if they still influe...Gautier Poupeau
 
Corrib.org - OpenSource and Research
Corrib.org - OpenSource and ResearchCorrib.org - OpenSource and Research
Corrib.org - OpenSource and Researchadameq
 
The Web of data and web data commons
The Web of data and web data commonsThe Web of data and web data commons
The Web of data and web data commonsJesse Wang
 
Web 3 Mark Greaves
Web 3 Mark GreavesWeb 3 Mark Greaves
Web 3 Mark GreavesMediabistro
 
Hello Open World - Semtech 2009
Hello Open World - Semtech 2009Hello Open World - Semtech 2009
Hello Open World - Semtech 2009Alexandre Passant
 
Vital AI: Big Data Modeling
Vital AI: Big Data ModelingVital AI: Big Data Modeling
Vital AI: Big Data ModelingVital.AI
 
The Information Workbench - Linked Data and Semantic Wikis in the Enterprise
The Information Workbench - Linked Data and Semantic Wikis in the EnterpriseThe Information Workbench - Linked Data and Semantic Wikis in the Enterprise
The Information Workbench - Linked Data and Semantic Wikis in the EnterprisePeter Haase
 
Linked Data MLA 2015
Linked Data MLA 2015Linked Data MLA 2015
Linked Data MLA 2015Cason Snow
 
Linked data MLA 2015
Linked data MLA 2015Linked data MLA 2015
Linked data MLA 2015Cason Snow
 
PoolParty Thesaurus Management Quick Overview
PoolParty Thesaurus Management Quick OverviewPoolParty Thesaurus Management Quick Overview
PoolParty Thesaurus Management Quick OverviewAndreas Blumauer
 
Semtech 2011 impressions
Semtech 2011 impressionsSemtech 2011 impressions
Semtech 2011 impressionsGeorge Roth
 

Similar to Linked data for Enterprise Data Integration (20)

Linked Data Tutorial
Linked Data TutorialLinked Data Tutorial
Linked Data Tutorial
 
PoolParty SKOS and Linked Data
PoolParty SKOS and Linked DataPoolParty SKOS and Linked Data
PoolParty SKOS and Linked Data
 
Paul houle resume
Paul houle resumePaul houle resume
Paul houle resume
 
Linked Data to Improve the OER Experience
Linked Data to Improve the OER ExperienceLinked Data to Improve the OER Experience
Linked Data to Improve the OER Experience
 
PoolParty Thesaurus Management - ISKO UK, London 2010
PoolParty Thesaurus Management - ISKO UK, London 2010PoolParty Thesaurus Management - ISKO UK, London 2010
PoolParty Thesaurus Management - ISKO UK, London 2010
 
X api chinese cop monthly meeting feb.2016
X api chinese cop monthly meeting   feb.2016X api chinese cop monthly meeting   feb.2016
X api chinese cop monthly meeting feb.2016
 
Why I don't use Semantic Web technologies anymore, event if they still influe...
Why I don't use Semantic Web technologies anymore, event if they still influe...Why I don't use Semantic Web technologies anymore, event if they still influe...
Why I don't use Semantic Web technologies anymore, event if they still influe...
 
Corrib.org - OpenSource and Research
Corrib.org - OpenSource and ResearchCorrib.org - OpenSource and Research
Corrib.org - OpenSource and Research
 
Semantic Web, e-commerce
Semantic Web, e-commerceSemantic Web, e-commerce
Semantic Web, e-commerce
 
Linked Data
Linked DataLinked Data
Linked Data
 
The Web of data and web data commons
The Web of data and web data commonsThe Web of data and web data commons
The Web of data and web data commons
 
The Semantic Data Web, Sören Auer, University of Leipzig
The Semantic Data Web, Sören Auer, University of LeipzigThe Semantic Data Web, Sören Auer, University of Leipzig
The Semantic Data Web, Sören Auer, University of Leipzig
 
Web 3 Mark Greaves
Web 3 Mark GreavesWeb 3 Mark Greaves
Web 3 Mark Greaves
 
Hello Open World - Semtech 2009
Hello Open World - Semtech 2009Hello Open World - Semtech 2009
Hello Open World - Semtech 2009
 
Vital AI: Big Data Modeling
Vital AI: Big Data ModelingVital AI: Big Data Modeling
Vital AI: Big Data Modeling
 
The Information Workbench - Linked Data and Semantic Wikis in the Enterprise
The Information Workbench - Linked Data and Semantic Wikis in the EnterpriseThe Information Workbench - Linked Data and Semantic Wikis in the Enterprise
The Information Workbench - Linked Data and Semantic Wikis in the Enterprise
 
Linked Data MLA 2015
Linked Data MLA 2015Linked Data MLA 2015
Linked Data MLA 2015
 
Linked data MLA 2015
Linked data MLA 2015Linked data MLA 2015
Linked data MLA 2015
 
PoolParty Thesaurus Management Quick Overview
PoolParty Thesaurus Management Quick OverviewPoolParty Thesaurus Management Quick Overview
PoolParty Thesaurus Management Quick Overview
 
Semtech 2011 impressions
Semtech 2011 impressionsSemtech 2011 impressions
Semtech 2011 impressions
 

More from Sören Auer

Knowledge Graph Research and Innovation Challenges
Knowledge Graph Research and Innovation ChallengesKnowledge Graph Research and Innovation Challenges
Knowledge Graph Research and Innovation ChallengesSören Auer
 
DBpedia - 10 year ISWC SWSA best paper award presentation
DBpedia  - 10 year ISWC SWSA best paper award presentationDBpedia  - 10 year ISWC SWSA best paper award presentation
DBpedia - 10 year ISWC SWSA best paper award presentationSören Auer
 
Project overview big data europe
Project overview big data europeProject overview big data europe
Project overview big data europeSören Auer
 
Open data for smart cities
Open data for smart citiesOpen data for smart cities
Open data for smart citiesSören Auer
 
The web of interlinked data and knowledge stripped
The web of interlinked data and knowledge strippedThe web of interlinked data and knowledge stripped
The web of interlinked data and knowledge strippedSören Auer
 
Проект Евросоюза LOD2 и Британский Институт Открытых данных
Проект Евросоюза LOD2 и Британский Институт Открытых данныхПроект Евросоюза LOD2 и Британский Институт Открытых данных
Проект Евросоюза LOD2 и Британский Институт Открытых данныхSören Auer
 
Linked data and semantic wikis
Linked data and semantic wikisLinked data and semantic wikis
Linked data and semantic wikisSören Auer
 
ESWC2010 "Linked Data: Now what?" Panel Discussion slides
ESWC2010 "Linked Data: Now what?" Panel Discussion slidesESWC2010 "Linked Data: Now what?" Panel Discussion slides
ESWC2010 "Linked Data: Now what?" Panel Discussion slidesSören Auer
 
LESS - Template-based Syndication and Presentation of Linked Data for End-users
LESS - Template-based Syndication and Presentation of Linked Data for End-usersLESS - Template-based Syndication and Presentation of Linked Data for End-users
LESS - Template-based Syndication and Presentation of Linked Data for End-usersSören Auer
 
Overview AG AKSW
Overview AG AKSWOverview AG AKSW
Overview AG AKSWSören Auer
 
WWW09 - Triplify Light-Weight Linked Data Publication from Relational Databases
WWW09 - Triplify Light-Weight Linked Data Publication from Relational DatabasesWWW09 - Triplify Light-Weight Linked Data Publication from Relational Databases
WWW09 - Triplify Light-Weight Linked Data Publication from Relational DatabasesSören Auer
 
Participatory Research
Participatory ResearchParticipatory Research
Participatory ResearchSören Auer
 

More from Sören Auer (12)

Knowledge Graph Research and Innovation Challenges
Knowledge Graph Research and Innovation ChallengesKnowledge Graph Research and Innovation Challenges
Knowledge Graph Research and Innovation Challenges
 
DBpedia - 10 year ISWC SWSA best paper award presentation
DBpedia  - 10 year ISWC SWSA best paper award presentationDBpedia  - 10 year ISWC SWSA best paper award presentation
DBpedia - 10 year ISWC SWSA best paper award presentation
 
Project overview big data europe
Project overview big data europeProject overview big data europe
Project overview big data europe
 
Open data for smart cities
Open data for smart citiesOpen data for smart cities
Open data for smart cities
 
The web of interlinked data and knowledge stripped
The web of interlinked data and knowledge strippedThe web of interlinked data and knowledge stripped
The web of interlinked data and knowledge stripped
 
Проект Евросоюза LOD2 и Британский Институт Открытых данных
Проект Евросоюза LOD2 и Британский Институт Открытых данныхПроект Евросоюза LOD2 и Британский Институт Открытых данных
Проект Евросоюза LOD2 и Британский Институт Открытых данных
 
Linked data and semantic wikis
Linked data and semantic wikisLinked data and semantic wikis
Linked data and semantic wikis
 
ESWC2010 "Linked Data: Now what?" Panel Discussion slides
ESWC2010 "Linked Data: Now what?" Panel Discussion slidesESWC2010 "Linked Data: Now what?" Panel Discussion slides
ESWC2010 "Linked Data: Now what?" Panel Discussion slides
 
LESS - Template-based Syndication and Presentation of Linked Data for End-users
LESS - Template-based Syndication and Presentation of Linked Data for End-usersLESS - Template-based Syndication and Presentation of Linked Data for End-users
LESS - Template-based Syndication and Presentation of Linked Data for End-users
 
Overview AG AKSW
Overview AG AKSWOverview AG AKSW
Overview AG AKSW
 
WWW09 - Triplify Light-Weight Linked Data Publication from Relational Databases
WWW09 - Triplify Light-Weight Linked Data Publication from Relational DatabasesWWW09 - Triplify Light-Weight Linked Data Publication from Relational Databases
WWW09 - Triplify Light-Weight Linked Data Publication from Relational Databases
 
Participatory Research
Participatory ResearchParticipatory Research
Participatory Research
 

Recently uploaded

National Institute of Standards and Technology (NIST) Cybersecurity Framework...
National Institute of Standards and Technology (NIST) Cybersecurity Framework...National Institute of Standards and Technology (NIST) Cybersecurity Framework...
National Institute of Standards and Technology (NIST) Cybersecurity Framework...MichaelBenis1
 
Centralized TLS Certificates Management Using Vault PKI + Cert-Manager
Centralized TLS Certificates Management Using Vault PKI + Cert-ManagerCentralized TLS Certificates Management Using Vault PKI + Cert-Manager
Centralized TLS Certificates Management Using Vault PKI + Cert-ManagerSaiLinnThu2
 
Microsoft x 2toLead Webinar Session 1 - How Employee Communication and Connec...
Microsoft x 2toLead Webinar Session 1 - How Employee Communication and Connec...Microsoft x 2toLead Webinar Session 1 - How Employee Communication and Connec...
Microsoft x 2toLead Webinar Session 1 - How Employee Communication and Connec...2toLead Limited
 
Java Optional (Kitworks Team Study 김성호 발표)
Java Optional (Kitworks Team Study 김성호 발표)Java Optional (Kitworks Team Study 김성호 발표)
Java Optional (Kitworks Team Study 김성호 발표)Wonjun Hwang
 
My Journey towards Artificial Intelligence
My Journey towards Artificial IntelligenceMy Journey towards Artificial Intelligence
My Journey towards Artificial IntelligenceVijayananda Mohire
 
Key projects in AI, ML and Generative AI
Key projects in AI, ML and Generative AIKey projects in AI, ML and Generative AI
Key projects in AI, ML and Generative AIVijayananda Mohire
 
CloudStack Authentication Methods – Harikrishna Patnala, ShapeBlue
CloudStack Authentication Methods – Harikrishna Patnala, ShapeBlueCloudStack Authentication Methods – Harikrishna Patnala, ShapeBlue
CloudStack Authentication Methods – Harikrishna Patnala, ShapeBlueShapeBlue
 
AI-Plugins-Planners-Persona-SemanticKernel.pptx
AI-Plugins-Planners-Persona-SemanticKernel.pptxAI-Plugins-Planners-Persona-SemanticKernel.pptx
AI-Plugins-Planners-Persona-SemanticKernel.pptxUdaiappa Ramachandran
 
Transcript: Trending now: Book subjects on the move in the Canadian market - ...
Transcript: Trending now: Book subjects on the move in the Canadian market - ...Transcript: Trending now: Book subjects on the move in the Canadian market - ...
Transcript: Trending now: Book subjects on the move in the Canadian market - ...BookNet Canada
 
Artificial Intelligence - AI For Everyone
Artificial Intelligence - AI For EveryoneArtificial Intelligence - AI For Everyone
Artificial Intelligence - AI For EveryoneSridhar Seshadri
 
Roundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdfRoundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdfMostafa Higazy
 
CloudStack Tooling Ecosystem – Kiran Chavala, ShapeBlue
CloudStack Tooling Ecosystem – Kiran Chavala, ShapeBlueCloudStack Tooling Ecosystem – Kiran Chavala, ShapeBlue
CloudStack Tooling Ecosystem – Kiran Chavala, ShapeBlueShapeBlue
 
Learning About GenAI Engineering with AWS PartyRock [AWS User Group Basel - F...
Learning About GenAI Engineering with AWS PartyRock [AWS User Group Basel - F...Learning About GenAI Engineering with AWS PartyRock [AWS User Group Basel - F...
Learning About GenAI Engineering with AWS PartyRock [AWS User Group Basel - F...Chris Bingham
 
Mind your App Footprint 🐾⚡️🌱 (@FlutterHeroes 2024)
Mind your App Footprint 🐾⚡️🌱 (@FlutterHeroes 2024)Mind your App Footprint 🐾⚡️🌱 (@FlutterHeroes 2024)
Mind your App Footprint 🐾⚡️🌱 (@FlutterHeroes 2024)François
 
Microsoft x 2toLead Webinar Session 2 - How Employee Learning and Development...
Microsoft x 2toLead Webinar Session 2 - How Employee Learning and Development...Microsoft x 2toLead Webinar Session 2 - How Employee Learning and Development...
Microsoft x 2toLead Webinar Session 2 - How Employee Learning and Development...2toLead Limited
 
Low Latency at Extreme Scale: Proven Practices & Pitfalls
Low Latency at Extreme Scale: Proven Practices & PitfallsLow Latency at Extreme Scale: Proven Practices & Pitfalls
Low Latency at Extreme Scale: Proven Practices & PitfallsScyllaDB
 
CloudStack 101: The Best Way to Build Your Private Cloud – Rohit Yadav, VP Ap...
CloudStack 101: The Best Way to Build Your Private Cloud – Rohit Yadav, VP Ap...CloudStack 101: The Best Way to Build Your Private Cloud – Rohit Yadav, VP Ap...
CloudStack 101: The Best Way to Build Your Private Cloud – Rohit Yadav, VP Ap...ShapeBlue
 
AI improves software testing to be more fault tolerant, focused and efficient
AI improves software testing to be more fault tolerant, focused and efficientAI improves software testing to be more fault tolerant, focused and efficient
AI improves software testing to be more fault tolerant, focused and efficientKari Kakkonen
 
iOncologi_Pitch Deck_2024 slide show for hostinger
iOncologi_Pitch Deck_2024 slide show for hostingeriOncologi_Pitch Deck_2024 slide show for hostinger
iOncologi_Pitch Deck_2024 slide show for hostingerssuser9354ce
 

Recently uploaded (20)

National Institute of Standards and Technology (NIST) Cybersecurity Framework...
National Institute of Standards and Technology (NIST) Cybersecurity Framework...National Institute of Standards and Technology (NIST) Cybersecurity Framework...
National Institute of Standards and Technology (NIST) Cybersecurity Framework...
 
Sue Loth: Job Search Strategies using personal connections
Sue Loth: Job Search Strategies using personal connectionsSue Loth: Job Search Strategies using personal connections
Sue Loth: Job Search Strategies using personal connections
 
Centralized TLS Certificates Management Using Vault PKI + Cert-Manager
Centralized TLS Certificates Management Using Vault PKI + Cert-ManagerCentralized TLS Certificates Management Using Vault PKI + Cert-Manager
Centralized TLS Certificates Management Using Vault PKI + Cert-Manager
 
Microsoft x 2toLead Webinar Session 1 - How Employee Communication and Connec...
Microsoft x 2toLead Webinar Session 1 - How Employee Communication and Connec...Microsoft x 2toLead Webinar Session 1 - How Employee Communication and Connec...
Microsoft x 2toLead Webinar Session 1 - How Employee Communication and Connec...
 
Java Optional (Kitworks Team Study 김성호 발표)
Java Optional (Kitworks Team Study 김성호 발표)Java Optional (Kitworks Team Study 김성호 발표)
Java Optional (Kitworks Team Study 김성호 발표)
 
My Journey towards Artificial Intelligence
My Journey towards Artificial IntelligenceMy Journey towards Artificial Intelligence
My Journey towards Artificial Intelligence
 
Key projects in AI, ML and Generative AI
Key projects in AI, ML and Generative AIKey projects in AI, ML and Generative AI
Key projects in AI, ML and Generative AI
 
CloudStack Authentication Methods – Harikrishna Patnala, ShapeBlue
CloudStack Authentication Methods – Harikrishna Patnala, ShapeBlueCloudStack Authentication Methods – Harikrishna Patnala, ShapeBlue
CloudStack Authentication Methods – Harikrishna Patnala, ShapeBlue
 
AI-Plugins-Planners-Persona-SemanticKernel.pptx
AI-Plugins-Planners-Persona-SemanticKernel.pptxAI-Plugins-Planners-Persona-SemanticKernel.pptx
AI-Plugins-Planners-Persona-SemanticKernel.pptx
 
Transcript: Trending now: Book subjects on the move in the Canadian market - ...
Transcript: Trending now: Book subjects on the move in the Canadian market - ...Transcript: Trending now: Book subjects on the move in the Canadian market - ...
Transcript: Trending now: Book subjects on the move in the Canadian market - ...
 
Artificial Intelligence - AI For Everyone
Artificial Intelligence - AI For EveryoneArtificial Intelligence - AI For Everyone
Artificial Intelligence - AI For Everyone
 
Roundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdfRoundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdf
 
CloudStack Tooling Ecosystem – Kiran Chavala, ShapeBlue
CloudStack Tooling Ecosystem – Kiran Chavala, ShapeBlueCloudStack Tooling Ecosystem – Kiran Chavala, ShapeBlue
CloudStack Tooling Ecosystem – Kiran Chavala, ShapeBlue
 
Learning About GenAI Engineering with AWS PartyRock [AWS User Group Basel - F...
Learning About GenAI Engineering with AWS PartyRock [AWS User Group Basel - F...Learning About GenAI Engineering with AWS PartyRock [AWS User Group Basel - F...
Learning About GenAI Engineering with AWS PartyRock [AWS User Group Basel - F...
 
Mind your App Footprint 🐾⚡️🌱 (@FlutterHeroes 2024)
Mind your App Footprint 🐾⚡️🌱 (@FlutterHeroes 2024)Mind your App Footprint 🐾⚡️🌱 (@FlutterHeroes 2024)
Mind your App Footprint 🐾⚡️🌱 (@FlutterHeroes 2024)
 
Microsoft x 2toLead Webinar Session 2 - How Employee Learning and Development...
Microsoft x 2toLead Webinar Session 2 - How Employee Learning and Development...Microsoft x 2toLead Webinar Session 2 - How Employee Learning and Development...
Microsoft x 2toLead Webinar Session 2 - How Employee Learning and Development...
 
Low Latency at Extreme Scale: Proven Practices & Pitfalls
Low Latency at Extreme Scale: Proven Practices & PitfallsLow Latency at Extreme Scale: Proven Practices & Pitfalls
Low Latency at Extreme Scale: Proven Practices & Pitfalls
 
CloudStack 101: The Best Way to Build Your Private Cloud – Rohit Yadav, VP Ap...
CloudStack 101: The Best Way to Build Your Private Cloud – Rohit Yadav, VP Ap...CloudStack 101: The Best Way to Build Your Private Cloud – Rohit Yadav, VP Ap...
CloudStack 101: The Best Way to Build Your Private Cloud – Rohit Yadav, VP Ap...
 
AI improves software testing to be more fault tolerant, focused and efficient
AI improves software testing to be more fault tolerant, focused and efficientAI improves software testing to be more fault tolerant, focused and efficient
AI improves software testing to be more fault tolerant, focused and efficient
 
iOncologi_Pitch Deck_2024 slide show for hostinger
iOncologi_Pitch Deck_2024 slide show for hostingeriOncologi_Pitch Deck_2024 slide show for hostinger
iOncologi_Pitch Deck_2024 slide show for hostinger
 

Linked data for Enterprise Data Integration

  • 1. Linked Data for Enterprise Information Integration Sören Auer
  • 2. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS The Web evolves into a Web of Data 2 Linked Open Data Facebook Open Graph
  • 3. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS The Evolution of the Web 3 Web 1.0 - Hypertext  Static Web pages  Hyperlinks  Link directories Web 2.0 – Social Apps  Social Web  Crowd-sourcing  Mashups Web 3.0 – Linked Data  REST APIs, RDF, JSON-LD  Vocabularies  Rich-snippets, Semantic Search 1990 2000 2010 Intranet 1.0 - Hypertext  Static Intranet pages  Keyword search  Hyperlinks Intranet 2.0 – Social Enterprise Apps  Salesforce  Crowd-sourcing  Mashups Intranet 3.0 – Enterprise Data Intranet  URI Scheme  Enterprise taxonomies / knowledge bases  RDB2RDF Mapping 1995 2005 2015 & Enterprise Intranets
  • 4. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Linked Data Principles 1. Use URIs to identify the “things” in your data 2. Use http:// URIs so people (and machines) can look them up on the web 3. When a URI is looked up, return a description of the thing (in RDF format) 4. Include links to related things http://www.w3.org/DesignIssues/LinkedData.html 4
  • 5. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Linked Enterprise Data Principles 1. Evolve existing existing taxonomies into enterprise knowledge bases/hubs 2. Establish a enterprise wide URI scheme 3. Equip existing information systems in your intranet with Linked Data interfaces 4. Establish links between related information 5
  • 6. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Linked Enterprise Data Advantages • Light-weight linked data integration complements more complex SOA architectures • Unified data (access) model simplifies data integration • Increase standardization while preserving diversity • Facilitate information flows along supply and value creation chains  Dramatically reduce data integration costs, increase enterprise flexibility 6
  • 7. Creating Knowledge out of Interlinked Data Inter-linking/ Fusing Classifi-cation/ Enrichment Quality Analysis Evolution / Repair Search/ Browsing/ Exploration Extraction Storage/ Querying Manual revision/ authoring Linked Data Lifecycle
  • 8. Creating Knowledge out of Interlinked Data Extraction Inter- linking Enrichm ent Quality Analysis Evolution Repair Explora- tion Extrac- tion Store Query Author ing
  • 9. Creating Knowledge out of Interlinked Data From unstructured sources • NLP, text mining, annotation From semi-structured sources • DBpedia, LinkedGeoData, DataCube From structured sources • RDB2RDF Extraction
  • 10. Creating Knowledge out of Interlinked Data Many different approaches: D2R, Virtuoso RDF Views, Triplify, No agreement on a formal semantics of RDF2RDF mapping • LOD readiness, SPARQL-SQL translation W3C RDB2RDF WG Extraction Relational Data Tool Triplify Sparqlify D2RQ Virtuoso RDF Views Technology Scripting languages (PHP) Java Java Whole middleware solution SPARQL endpoint - X X X Mapping language SQL SPARQL CONSTRUCT Views + SQL RDF based RDF based Mapping generation Manual Semi- automatic Semi- automatic Manual Scalability Medium- high (but no SPARQL) Very high Medium High Malhotra, Auer, Erling, Hausenblas: W3C RDB2RDF Incubator Group Report. W3C RDB2RDF Incubator Group, 2009.
  • 11. Creating Knowledge out of Interlinked Data • Rationale: Exploit existing formalisms (SQL, SPARQL Construct) as much as possible • flexible & versatile mapping language • translating one SPARQL query into exactly one efficiently executable SQL query • Solid theoretical formalization based on SPARQL-relational algebra transformations • Extremely scalable through elaborated view candidate selection mechanism • Used to publish 20B triples for LinkedGeoData Sparqlify Stadler, Unbehauen, Auer, Lehmann: Sparqlify – Very Large Scale Linked Data Publication from Relational Databases. Submitted to VLDB-Journal. SPARQL Construct SQL View Bridge
  • 12. Creating Knowledge out of Interlinked Data Storage and Querying Inter- linking Enrichm ent Quality Analysis Evolution Repair Explora- tion Extrac- tion Store Query Author ing
  • 14. Creating Knowledge out of Interlinked Data 1. Semantic (Text) Wikis • Authoring of semantically annotated texts 2. Semantic Data Wikis • Direct authoring of structured information (i.e. RDF, RDF-Schema, OWL) Two Kinds of Semantic Wikis
  • 15. Creating Knowledge out of Interlinked Data The situation at Daimler (€97.76 billion revenue, 250.000 employees): • 3.000 heterogeneous IT systems • Different units (car, bus, truck etc.) with very different views • No common language • Inability to identify crucial entities (parts, locations etc.) enterprise wide There is no (can not be a) single Enterprise Information Model A distributed, iterative, bottom-up integration approach such as Linked Data might be able to help (pay-as-you-go). Can Linked Data help to solve the EII problem in a fortune-500 company?
  • 16. Creating Knowledge out of Interlinked Data 16 Search before
  • 17. Creating Knowledge out of Interlinked Data
  • 18. Creating Knowledge out of Interlinked Data OntoWiki with loaded car model data
  • 19. Creating Knowledge out of Interlinked Data Management of Enterprise Taxonomies with OntoWiki Based on the W3C SKOS standard Corporate Language Management at Daimler: 500k concepts in 20 languages
  • 20. Creating Knowledge out of Interlinked Data Search after Showing recommondations from the knowledge base integrating car model data and enterprise taxonomy
  • 21. Creating Knowledge out of Interlinked Data You can search for „Kombi“ (station wagon) and find T- Models (Daimler term for station waggon)
  • 22. FromIntranettoEnterpriseDataWebaroundaknowledgehub Auer, Frischmuth, Klímek, Unbehauen, Holzweißig, Marquardt: Linked Data in Enterprise Information Integration Submitted to Semantic Web Journal 2012.
  • 23. Creating Knowledge out of Interlinked Data © CC-BY-NC-ND by ~Dezz~ (residae on flickr) Linking Inter- linking Enrichm ent Quality Analysis Evolution Repair Explora- tion Extrac- tion Store Query Author ing
  • 24. Creating Knowledge out of Interlinked Data In an uncontrolled environment as the Data Web, there will be a proliferation of equivalent or similar entity identifiers Manual Link discovery: • Sindice integration into UIs • Semantic Pingback Semi-automatic: • SILK • LIMES Automatic/ Supervised: • Raven [1] Linking Entities on the Data Web [1] Ngonga, Lehmann, Auer, Höffner: RAVEN -- Active Learning of Link Specifications, OM@ISWC, 2011.
  • 25. Creating Knowledge out of Interlinked Data Enrichment Inter- linking Enrichm ent Quality Analysis Evolution Repair Explora- tion Extrac- tion Store Query Author ing
  • 26. Creating Knowledge out of Interlinked Data Linked Data is mainly instance data!!! ORE (Ontology Repair and Enrichment) tool allows to improve an OWL ontology by fixing inconsistencies & making suggestions for adding further axioms. • Ontology Debugging: OWL reasoning to detect inconsistencies and satisfiable classes + detect the most likely sources for the problems. user can create a repair plan, while maintaining full control. • Ontology Enrichment: uses the DL-Learner framework to suggest definitions & super classes for existing classes in the KB. works if instance data is available for harmonising schema and data. http://aksw.org/Projects/ORE Enrichment & Repair Lehmann, Auer, Tramp: Class Expression Learning for Ontology Engineering. Journal of Web Semantics (JWS), 2011.
  • 27. Creating Knowledge out of Interlinked Data Analysis Quality Inter- linking Enrichm ent Quality Analysis Evolution Repair Explora- tion Extrac- tion Store Query Author ing CC BY SA Wikipedia
  • 28. Creating Knowledge out of Interlinked Data Quality on the Data Web is varying a lot • Hand crafted or expensively curated knowledge base (e.g. DBLP, UMLS) vs. extracted from text or Web 2.0 sources (DBpedia) Research Challenge • Establish measures for assessing the authority, provenance, reliability of Data Web resources Opportunity for EII: Employ crowd-sourced knowledge from the Data Web in the Enterprise Linked Data Quality Analysis FP7-IP DIACHRON Managing the Evolution and Preservation of the Data Web Started April 2013
  • 29. Creating Knowledge out of Interlinked Data Evolution © CC-BY-SA by alasis on flickr) Inter- linking Enrichm ent Quality Analysis Evolution Repair Explora- tion Extrac- tion Store Query Author ing
  • 30. Creating Knowledge out of Interlinked Data Exploration Inter- linking Enrichm ent Quality Analysis Evolution Repair Explora- tion Extrac- tion Store Query Author ing
  • 31. Creating Knowledge out of Interlinked Data An ecosystem of LOD visualizations LODExploration Widgets Spatial faceted- browsing Faceted- browsing Statistical visualization Entity-/faceted- Based browsing Domain specific visualizations … … LODDatasetsChoreography layer • Dataset analysis (size, vocabularies, property histograms etc.) • Selection of suitable visualization widgets Brunetti, Auer, García: The Linked Data Visualization Model. To appear in IJSWIS, 2012.
  • 32. Creating Knowledge out of Interlinked Data LOD Life-(Washing-)cycle supported by Debian based LOD2 Stack http://stack.lod2.eu
  • 33. Creating Knowledge out of Interlinked Data Linked Enterprise Intra Data Webs fill the gap between Intra-/Extranets and EIS/ERP Unstructured Information Management Structured Information Management Support the long tail of enterprise information domains • Human-resources • Requirements engineering • Supply-chains
  • 34. Creating Knowledge out of Interlinked Data • Linked Data is a promising technology for closing the gap between SOA and unstructured information management • wealth of knowledge available as LOD can be leveraged as background knowledge for Enterprise applications • The application of Linked Data in the enterprise is still largely unexplored (opportunity) • Linked Data will make Enterprise Information Integration more flexible, iterative, cost effective Take home messages Auer, Frischmuth, Klímek, Tramp, Unbehauen, Holzweißig, Marquardt: Linked Data in Enterprise Information Integration Submitted to Semantic Web Journal.
  • 35. Creating Knowledge out of Interlinked Data Thanks for your attention! Sören Auer http://www.informatik.uni-leipzig.de/~auer | http://aksw.org | http://lod2.org auer@cs.uni-bonn.de

Editor's Notes

  1. http://www.flickr.com/photos/residae/2560241604/#/
  2. http://www.flickr.com/photos/alasis/3541341601/sizes/l/in/photostream/