Building an Ontological Base for Experimental

Evaluation of Semantic Web Applications

Peter Bartalos, Michal Barla, Gyorgy Frivolt, Michal Tvarožek,

Anton Andrejko, Mária Bieliková and Pavol Návrat

{name.surname}@fiit.stuba.skInstitute of Informatics and Software Engineering

Faculty of Informatics and information Technologies Slovak University of Technology in Bratislava

Motivation

• Semantic Web applications Experimental Evaluation (SWEE)– Semantic annotation of the information

– Searching in semantic information space

• AKTORS

• Knowledge Web

• On-To-Knowledge

• NAZOU – job offers (nazou.fiit.stuba.sk) Tools for acquisition, organization and maintenance of knowledge in an

environment of heterogeneous information resources

• MAPEKUS – scientific publication (mapekus.fiit.stuba.sk)Modeling and Acquisition, Processing and Employing Knowledge About User Activities in the Internet Hyperspace

• Demand for well-built large scale ontologies with specific properties

• Filling the ontology with instances (not it’s creation) – building the A-box

Outline

• Approaches to ontological base creation

• Method for ontological test base building

• Evaluation

• Conclusions

Filling the ontology with instances

jo:JobOffer

jo:hasPrerequisite*

jo:offersPosition

jo:Organization

jo:isOfferedByjo:isOfferedVia

jo:hasBenefit*

jo:hasApplyInformation*

r:Region

jo:hasDutyLocation*

jo:Salary

jo:hasSalary

jo:offers*jo:mediates*

jo:isBasedAt

r:isPartOf* r:consistsOf*

jo:ApplyInformation

c:ProfessionClassification

jo:Prerequisite

jo:Benefit

Web

3) Wrappers

1) Generic editor

4) Generators

2) Specialized editor

SWEE OntologyFile HelpEdit

Profession

Clerks

Armed Forces

Lorem

Lorem

lor

Enter Text

Edit

lor

Lorem IpsimSaldksa;d saD sadSasadsa d’sadsaSalkdjlkfjd fld;skfDlks ljflkdsjfdsf kldsf dsdskjfldsk fj

Edit

Specialized editorSpecialized editor

jo:JobOffer

jo:hasPrerequisite*

jo:offersPosition

jo:Organization

jo:isOfferedByjo:isOfferedVia

jo:hasBenefit*

jo:hasApplyInformation*

r:Region

jo:hasDutyLocation*

jo:Salary

jo:hasSalary

jo:offers*jo:mediates*

jo:isBasedAt

r:isPartOf* r:consistsOf*

jo:ApplyInformation

c:ProfessionClassification

jo:Prerequisite

jo:Benefit

Generic editorGeneric editor

Profession

Clerks

Armed ForcesLorem Edit

Manual approaches

Automatic approaches

Generic ontology editors

• Understand the generic structure of the ontology

• Immediately usable

• Domain independent

• Insufficient validation and user comfort

• Suitable for experts (ontology engineers)

jo:JobOffer

jo:hasPrerequisite*

jo:offersPosition

jo:Organization

jo:isOfferedByjo:isOfferedVia

jo:hasBenefit*

jo:hasApplyInformation*

r:Region

jo:hasDutyLocation*

jo:Salary

jo:hasSalary

jo:offers*jo:mediates*

jo:isBasedAt

r:isPartOf* r:consistsOf*

jo:ApplyInformation

c:ProfessionClassification

jo:Prerequisite

jo:Benefit

Generic editorGeneric editor

Profession

Clerks

Armed ForcesLorem Edit

Generic ontology editors

Specialized ontology editors

• Freedom in adjusting to a given ontology and user requirements

• Sophisticated validation

based on the knowledge

of the ontology

• Development and maintenance costs

• Coupled to a ontology

• Suitable also for non-experts

File HelpEdit

Profession

Clerks

Armed Forces

Lorem

Lorem

lor

Enter Text

Edit

lor

Lorem IpsimSaldksa;d saD sadSasadsa d’sadsaSalkdjlkfjd fld;skfDlks ljflkdsjfdsf kldsf dsdskjfldsk fj

Edit

Specialized editorSpecialized editor

Specialized ontology editors

JOE – Job Offer Editor

Wrappers

• Parse Web pages and produce structured output

• Need well structured pages

• Do not need a human involvement

• Significant amount of acquired data

• Development and maintenance costs

Generators

• Reusing the already existing data

• Increase the size of the ontological base

• Instances of desired properties

• Development and maintenance costs

• Meaningfulness of the data

Approaches to Ontological Base Creation

• Different approaches have different benefits and disadvantages

• They support each other

• They can be adjusted

– Invested time

– Development of tools

Method of Ontological Base Creation

• Specification of the requirements for the ontology

– Amount of data

– Range of properties of the instances

– Instance detail

– Quality

• Analysis of the domain and information sources

• Generally no approach can separately satisfy the requirements

• Adjusting the manual and automatic approaches

Method of Ontological Base Creation

Web

) 3 Wrappers

SWEE Ontology

1jo:JobOffer

jo:hasPrerequisite*

jo:offersPosition

jo:Organization

jo:isOfferedByjo:isOfferedVia

jo:hasBenefit*

jo:hasApplyInformation*

r:Region

jo:hasDutyLocation*

jo:Salary

jo:hasSalary

jo:offers*jo:mediates*

jo:isBasedAt

r:isPartOf* r:consistsOf*

jo:ApplyInformation

c:ProfessionClassification

jo:Prerequisite

jo:Benefit

Generic editorGeneric editor

Profession

Clerks

Armed ForcesLorem Edit

) Generic editor

editor2) Specialized

File HelpEdit

Profession

Clerks

Armed Forces

Lorem

Lorem

lor

Enter Text

Edit

lor

Lorem IpsimSaldksa;d saD sadSasadsa d’sadsaSalkdjlkfjd fld;skfDlks ljflkdsjfdsf kldsf dsdskjfldsk fj

Edit

Specialized editorSpecialized editor 4) Generators

Satisfaction of the requirements to ontological data

Amount Range ofproperties

Details Resamblence toreal data

Sat

isfa

ctio

n o

f re

qu

irem

ents

Satisfaction of the requirements to ontological data

• Generic editor

Amount Range ofproperties

Details Resamblence toreal data

Sat

isfa

ctio

n o

f re

qu

irem

ents

Satisfaction of the requirements to ontological data

• Generic editor

• Specialized editor

Amount Range ofproperties

Details Resamblence toreal data

Sat

isfa

ctio

n o

f re

qu

irem

ents

Satisfaction of the requirements to ontological data

• Generic editor

• Specialized editor

• Wrappers

Amount Range ofproperties

Details Resamblence toreal data

Sat

isfa

ctio

n o

f re

qu

irem

ents

Satisfaction of the requirements to ontological data

• Generic editor

• Specialized editor

• Wrappers

• GeneratorsAmount Range of

propertiesDetails Resamblence to

real data

Sat

isfa

ctio

n o

f re

qu

irem

ents

Evaluation of the method

• NAZOU (nazou.fiit.stuba.sk)

– Ontology consists of 740 classes (670 belong to taxonomies)

– All approaches used

• MAPEKUS (mapekus.fiit.stuba.sk)

– Ontology consists of 390 classes (360 belong to taxonomies)

– Only one approach used

Conclusions

• Solution for building ontologies for semantic Web application experimental evaluation

• Tunable method based on different approaches of ontology instance creation

• Evaluated in the domain of job offers and scientific publication

• Developed two SWEE ontologies

– Job offer ontology

– Publication metadata ontology