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LOD2 Webinar . 29.11.2011 . Page 1 http://lod2.eu

Creating Knowledge out of Interlinked Data



http://lod2.eu

LOD2 is a large-scale integrating project co-funded by the European

Commission within the FP7 Information and Communication Technologies

Work Programme. This 4-year project comprises leading Linked Open

Data technology researchers, companies, and service providers. Coming

from across 12 countries the partners are coordinated by the Agile

Knowledge Engineering and Semantic Web Research Group at the

University of Leipzig, Germany.

LOD2 will integrate and syndicate Linked Data with existing large-scale

applications. The project shows the benefits in the scenarios of Media and

Publishing, Corporate Data intranets and eGovernment.



http://lod2.eu

Once per month the LOD2 webinar series offer a free webinar about tools and services along the Linked Open Data Life Cycle. Stay with us and learn more about acquisition, editing, composing, connected applications – and finally publishing Linked Open Data.



LIMES - Link Discovery Framework for Metric Spaces -



• LIMES in LOD2

• Main Ideas

• Technical Details

• Using LIMES

– The „Geeky“ Approach

– LIMES Interface

– Assisted Linking

Overview



Linked Data Lifecycle

Inter-linking/ Fusing

Classifi-cation/

Enrichment

Quality Analysis

Evolution / Repair

Search/ Browsing/

Exploration

Extraction

Storage/ Querying

Manual revision/ authoring

Linked Data

Lifecycle



LOD2 Stack

LOD2 Services

Central LOD2 Services Distributed/Local LOD2 Components

LOD Cloud: Access interfaces:

LOD2 Stack UI components

LOD2 Stack APIs and components

Knowledge Storage Layer

Linked Data SPARQL DUMPS

Sindice

Sig.ma

Semantic Authoring

LOD Cloud hosted on OpenLink's Virtuoso Query and Browsing capability

GovData.eu eGovernment

Portal Interlinking API

SILK DXX

Knowledge Base Fusion API

SemMF WIQA

Triplify, D2R

Enrichment and Repair API

DL-Learner ORE

Multi-Domain Ontology

Exalead

Web Search

Enterprise Search

LOD2 STACK API Create

Structure

Link

Fuse

Browse & Structure

Knowledge Store API

Virtuoso + MonetDB

Wolters Kluwer Deutschland

LOD2 applied to Media and Publishing

LIMES



• Characteristics

– Very large data sets

– Complex data sets

• Problems

– Runtime

– Complex Specifications

• Solutions

– Time-efficient computation

– Assistance during configuration

– Machine learning for creating link specifications

Link Discovery



• Declarative Link Discovery Framework

• Tuned towards efficiency and extensibility

• Set-theoretical grammar for specifying links

• Time-efficient mappers for single data types

• Machine learning for detecting link specs

LIMES



Architecture

Mac

hin

e L

ear

nin

g



Workflow



Workflow

Hybrid approach

Time-efficient mappers Rich grammar



1. Metadata

2. Source and Target

3. Similarity Measure

4. Acceptance Conditions

5. Review Conditions

6. Execution Mode

7. Output Format

LIMES Link Specifications



1. Metadata





6. Execution Mode

7. Output Format




1. Metadata





6. Execution Mode

7. Output Format




• Preprocessing functions

– Strings, numerical values

– Data converters

• Similarity Measures

– String

– Numerical values


Trigram

label label

lowerCase



• Operators

– Measure operators

– Spec operators


Trigram

label label

Trigram

label name

MAX



• Operators

– Measure operators

– Spec operators


Trigram

label label

Trigram

label name

Filter Filter

OR



1. Metadata





6. Execution Mode

7. Output Format




• Task: Link drugs

and ingredients

– Source: Dailymed

– Target: Drugbank

– Features

• Definition of source, target, measures

• Using property chains for linking

• Using preprocessing

Geeky approach: XML



• Task: Link drugs

across knowledge bases

– Source: DBpedia

– Target: Drugbank

– Features

• Definition of complex measures

LIMES Native Interface



• OR(trigram(x.rdfs:label, y.drugbank:genericName)|0.8,

trigram(x.rdfs:label, y.rdfs:label)|0.8)

LIMES Native Interface

Trigram

label label

Trigram

label genericName

Filter Filter

OR



• Task: Link diseases

across knowledge bases

– Source: Diseasome

– Target: Sider

– Features

• Assisted linking

• Definition of complex measures

COLANUT



• Technical Details

– Requirements: Java 1.6

– License: http://creativecommons.org/licenses/

by-nc-sa/3.0/

• Technical papers

– Axel-Cyrille Ngonga Ngomo: A Time-Efficient Hybrid Approach to Link

Discovery. In: Proceedings of the sixth international workshop on

Ontology Matching, 2011

– Axel-Cyrille Ngonga Ngomo und Klaus Lyko: EAGLE: Efficient Active

Learning of Link Specifications using Genetic Programming. In:

Proceedings of ESWC 2012

– Axel-Cyrille Ngonga Ngomo, Jens Lehmann, Sören Auer und Konrad

Höffner: RAVEN -- Active Learning of Link Specifications. In: Proceedings

of OM@ISWC

Further Information



Credits

Jingle Axel Ngonga

Coordination Thomas Thurner

Martin Kaltenböck

Moderation Martin Kaltenböck

Presented by Axel Ngonga

http://bis.uni-leipzig.de/AxelNgonga

[email protected]






http://lod2.eu

Hope you enjoyed staying with us – if you need more detailed information, visit us at www.lod2.eu and let us know how we can improve to meet your expectations! Don’t forget to register for our next webinar 24.04.2012 – D2R (University of Leipzig)