asun gomez perez's presentation at sssw 2011

© A. Gómez Pérez, M.C. Suarez de Figueroa, B. Villazón, E.Montiel, G. Aguado, M. Espinoza1Ontological Engineering

Ontology Engineering and Resource Re-Engineering

Asunción Gómez-Pérez ([email protected])

Credits to: Boris Villazón-Terrazas ([email protected])

Mari Carmen Suárez -Figueroa ([email protected])

Work distributed under the license Creative Commons Attribution-Noncommercial-Share Alike 3.0

mailto:[email protected]�

mailto:[email protected]�


Index Motivation

State of the Art on Methodologies for Ontology Engineering

Building an ontology

Conclusion


Motivation

In our team, we want to build an OWL ontology inthe geographical domain, but we want to useseveral geographical standardized terminologystored in DBs and classification schemes in ourown format. I want to combine it with statisticinformation about unemployment

Non Ontological Resource Reengineering

Non Ontological Resource Reuse

Classical


Where is the terminology?DBs from a Geographical institute

Heterogeneity.- Language.- Terminology.- Granularity

Catalog/ID

Implicit knowledgecoded in numbers

XX-YY-ZZ02-01-0202: transportation01: road02: 3-lines highway


Different Data Models with the same information


Lot of terminologies being used …

Music

Geographic Life Sciences

PublicationsE-Gov

On-line activities

Cross-domains


Tools for searching vocabularies

7

Linked Open Vocabularies

http://schemaweb.info

http://swoogle.umbc.edu/

http://labs.mondeca.com/dataset/lov

http://watson.kmi.open.ac.uk/WatsonWUI/



After some proces….


Geolinkeddata ontologies

Ontology Network

hasStatisticalData

on

Ontology

Specification

Legend

hydrOntology

4

FAO

FAO Geopolitical ontology

WGS84

4W3C Vocabulary

GML

4GML Specification

O. Statistics

SCOVO

O. Time

W3C Time

hasLat/Long

hasGeometry

hasLat/Long

hasGeometry

hasLocation/isLocated

Thesaurus

UNESCO

4EGM / ERM

GeoNames…

scv:Dimensionscv:Item

scv:Dataset

WGS84 Geo Positioning: an RDF

vocabulary

hydrographical phenomena (rivers,

lakes, etc.)

Ontology for OGC Geography Markup Language

Vocabulary for instants, intervals, durations, etc.

Names and international code systems for territories and groups

SCOVO

hydrOntology

Time ontology


Motivation

In our team, we want to build an ontology about thehuman resources management domain. Theontology should include information aboutoccupations and activity sectors, data must be keptin the original DBs, and we want to have theontology in several natural languages.

Classical

Re-engineering Non-ontological resources

Ontological Resource Reuse

Localizing Ontological Resources

Ontology

Mappings

Ontology-DB mapping


Index

Motivation



Conclusion


Building ontologies in the 1990s and 2000s

Methodologies for building single ontologies do notconsider the reuse of knowledge

• Uschold and King’s method• Grüninger and Fox’s methodology• KACTUS approach• METHONTOLOGY • SENSUS method• On-To-Knowledge• DILIGENT

Ontology learning approaches for building ontologies fromstructured, semi-structured and non-structured data

• Are not integrated with current methodologies• Mainly from non-structured data using NLP techniques


Current situation

• Reuse of knowledge-aware resources– Already consensuated by domain experts

• Ontologies are built collaboratively• Ontologies are connected in ontology

networks• Multilingual features

OntologyDevelopmentProcess

© A. Gómez Pérez, M.C. Suarez de Figueroa, B. Villazón, E.Montiel, G. Aguado, M. Espinoza14Ontological Engineering14

Knowledge Resources

Non Ontological ResourceReuse

Non Ontological ResourceReengineering

2

2

2

Non Ontological Resources

Thesauri

DictionariesGlossaries Lexicons

TaxonomiesClassificationSchemas

O. Localization9

Ontology Support Activities: Knowledge Acquisition (Elicitation); Documentation; Configuration Management; Evaluation (V&V); Assessment

1,2,3,4,5,6,7,8, 9

Ontological ResourceReengineering

4

4

4

O. Aligning

O. Merging

Alignments5

5

5

6

6

6

6

3

Ontological ResourceReuse

3Ontological Resources

O. Repositories and RegistriesFlogic

RDF(S)OWL

Ontology DesignPattern Reuse

7

O. Design Patterns

Ontology Restructuring(Pruning, Extension,

Specialization, Modularization)

8O. Specification O. Conceptualization O. ImplementationO. Formalization

1RDF(S)

OWL

FlogicScheduling

NeOn Scenarios


NeOn Methodology

Process and activities covered:

Ontology Specification

Scheduling

Non-Ontological Resource Reuse

Non-Ontological Resource Re-engineering

Reuse General Ontologies

Reuse Domain Ontologies

Reuse Ontology Statements

Reuse Ontology Design Patterns

All processes and activities are described with:

A filling card

A workflow

Examples


Handbook on the NeOn Methodology

Slide 16

http://www.neon-project.org/nw/NeOn_Book

© A. Gómez Pérez, M.C. Suarez de Figueroa, B. Villazón, E.Montiel, G. Aguado, M. Espinoza17Ontological EngineeringSlide 17

Slide 17

22 Executive Chapter Summaries are available at the NeOn Web Site


Index

Motivation



Conclusion


oES

EURESES (Int)

gES

LombardES (It)

qES

rES

pES

aES

cES

iES

nES

eES

hES

lES

fESd

ES

mES

WalloniaES (Be)

bES

PrivateES (Int)

CataloniaES (Es)

ES

LEGENDA

CandCand..CandCand..

VacanVacan..VacanVacan..

VacanVacan..VacanVacan.. CandCand..CandCand..


CandCand..CandCand..VacanVacan..VacanVacan..




Employment Service

Job Seeker’s Candidacy

Employer Job Vacancy

Looking for an European Employment


gES

LombardES (It)

qES

rES

pES

aES

cES

iES

nES

eES

hES

lES

oES

fESd

ES

mES

bES

Requester ES

Responding ES

ES not involved

Job Seeker’s Candidacy

Employer Job Vacancy

LEGENDA

Helping Job Seekers on their way

EuropeanEmployment

MediatorsMarketplace

LocalMatching algorithm

EURESES (Int)

LocalMatching algorithmPrivate

ES (Int)Local

Matching algorithm

WalloniaES (Be)

LocalMatching algorithm

CataloniaES (Es)











VacanVacan..VacanVacan.. VacanVacan..VacanVacan..




Key issues

• Reuse of proprietary knowledge-aware resources

• Heterogeneity– Terms are in different languages– Different conceptualization (different ways of

organizing job categories)– Different DB schemas

• Data must be kept in the original sources and in their own language.


Key aspects of Ontological Engineering• Ontologies

– Single versus network of ontologies?– Are ontologies built from scratch or reusing knowledge-aware

resources?– Are mappings used for solving conceptual mistmaches?

• Instances– Where are the data/instances?

• Instances are in the ontology• Instances are in RDF files independently of the ontology• Data are kept in the original sources

– Are instances distributed or centralized?– Have instances a very high rate of changes?– Heterogeneous provenance of instances– Degrees of data quality– Permissions


Ms Ms

Ms

Ms

Ms

MsMs

Ms

Ms

Ms

Centralized network of ontologies where data are

distributed

1. Build a reference ontology

Federated network of ontologieswhere data are distributed

1. Build a reference ontology for the domain2. Build local ontologies3. Build mappings between the core and local ontologies4. Build mappings between the local ontologies and the data

sources

MsMs

Ms

MsMs

2. Build mappings between the reference ontology and the data sources


Knowledge Resources



2

2

2


Thesauri



O. Localization9


1,2,3,4,5,6,7,8, 9


4

4

4

O. Aligning

O. Merging

Alignments5

5

5

6

6

6

6

3




RDF(S)OWL


7

O. Design Patterns




1RDF(S)

OWL

FlogicScheduling

NeOn Methodology


Ontology Requirement Specification Document

Ontology Requirements Specification Document Template

1 Purpose

“Software developers and ontology practitioners should include in this slot the purpose of the ontology”

2 Scope

“Software developers and ontology practitioners should include in this slot the scope of the ontology”

3 Level of Formality

“Software developers and ontology practitioners should include in this slot the level of formality of the ontology”

4 Intended Users

“Software developers and ontology practitioners should include in this slot the intended users of the ontology”

5 Intended Uses

“Software developers and ontology practitioners should include in this slot the intended uses of the ontology”

6 Groups of Competency Questions

“Software developers and ontology practitioners should include in this slot the groups of competency questions and their answers, including priorities for each group”

7 Pre-Glossary of Terms

Terms

“Software developers and ontology practitioners should include in this slot the list of terms included in the CQs and their frequencies”

Objects


Ontology Specification:Identify requirements using competency questions


Ontology Specification. The Ontology Requirement Specification

Document


Knowledge Resources



2

2

2


Thesauri



O. Localization9


1,2,3,4,5,6,7,8, 9


4

4

4

O. Aligning

O. Merging

Alignments5

5

5

6

6

6

6

3




RDF(S)OWL


7

O. Design Patterns




1RDF(S)

OWL

FlogicScheduling

NeOn Methodology


Searching Resources

• Use the terminology from the ORSD

• Find resources covering the terminologyKnowledge Resources

Ontological Resources

O. Design Patterns

2


Thesauri




RDF(S)OWL

• Where: - Internet- Standardization bodies (ISO,…)- Intranet of the organization- Ontology Registries



Search and Selectnon-ontological resources

• We select the most appropriate standards and taxonomies for:

– Occupation ClassificationISCO-88 (COM), SOC, ISCO-88, ONET, Eures Taxonomy.

– Classification of Economic Activities

ISIC Rev. 3.1, NACE Rev. 1.1, NAICS

– Apprenticeship classificationsISCED 97, FOET

– Currency ClassificationISO 4217

– Geography ClassificationISO 3166, Eures Taxonomy

Language ClassificationISO 6392, CEF

Driving License ClassificationEuropean Legislation

Skill ClassificationEures Taxonomy

Contract Types ClassificationLE FOREM, Eures and BLL Classification

Work Condition ClassificationLE FOREM, Eures and BLL Classification

Is the terminology included in the Ontology Requirements Specification Document

covered by the resources?


ISO 4217 (currencies) ISO 3166 (countries)


Multilingual Non-ontological resources - ISCO-88 (COM)


Searching OntologiesOntology Requirement Specification Document

• Search ontologies • Compare and Assess ontologies• Select the best ontology based on

– Coverage of the domain– Expressivity of the Implementation language


Knowledge Resources



2

2

2


Thesauri



O. Localization9


1,2,3,4,5,6,7,8, 9


4

4

4

O. Aligning

O. Merging

Alignments5

5

5

6

6

6

6

3




RDF(S)OWL


7

O. Design Patterns




1RDF(S)

OWL

FlogicScheduling

NeOn Methodology


Gantt chart for your project. Waterfall model


Reuse and Re-engineer ing + Incremental

Slide 36


Knowledge Resources



2

2

2


Thesauri



O. Localization9


1,2,3,4,5,6,7,8, 9


4

4

4

O. Aligning

O. Merging

Alignments5

5

5

6

6

6

6

3




RDF(S)OWL


7

O. Design Patterns




1RDF(S)

OWL

FlogicScheduling

NeOn Methodology


Motivation

I want to transform myadjacency list-basedclassification into anontology


Types of non-ontological resources

Non-OntologicalResources areknowledge-awareresources whosesemantics have notbeen formalized yetby means of anontology


Types of non-ontological resources


Approaches to transformresources into ontologies

ABox

TBox

Population


Approach for Re-engineering Non-OntologicalResources


Patterns for Re-engineering Classification Schemes into Ontologies

– ABox transformation

– TBox transformation


Template for the PR-NOR

© A Method for Reusing and Re-engineering Non-Ontological

INPUT

OUTPUT

PROCESS

Re-engineering NORs


Pattern for re-engineering a classification scheme, which follows the adjacency list data model, into an ontology schema

Patterns for Re-engineering Classification Schemes

INPUT: Non-Ontological Resource

General

Example

OUTPUT: Ontology GeneratedGeneral

Example

ExamplePROCESS: How to Re-

engineer


PR-NOR library at the ODP PortalTechnological support

http://mccarthy.dia.fi.upm.es/nor2o/

NOR2O: a Library for TransformingNon-Ontological Resources to Ontologies

http://mccarthy.dia.fi.upm.es/nor2o/�


Pattern based approach for re-engineering non ontological resources

ISCO-88 (COM)International Standard Classification

of Occupations (for European Union purposes)

FOETClassification of fields of education and training

NACEStatistical Classification of Economic Activities in the

European Community

ISTATItalian Geography

Standard

Pattern for re-engineering a classification scheme modelled

with a Path Enumeration Data Model

Pattern for re-engineering a classification scheme modelled

with an Adjacency List Data ModelItalian

GeographyOntology

EconomicActivity Ontology

EducationOntology

OccupationOntology

ISO 3166English country names

and code elements

Pattern for re-engineering a classification scheme modelled with a Snowflake Data Model Geography

Ontology


ISO 3166-1 (XML) Regions Table(Eures Oracle DB)

….

<ISO_3166-1_Entry><ISO_3166-1_Country_name>SPAIN</ISO_3166-1_Country_name><ISO_3166-1_Alpha-2_Code_element>ES</ISO_3166-1_Alpha-2_Code_element>

</ISO_3166-1_Entry>…

Location

Country Region

subClass-Of

has region

Spain Cataluña

Canarias

Galicia

Andalucía

Ontology model

Ontology instances

Excerpt of the Geography Ontology

Knowledge Resource Re-engineering and Aggregation


Knowledge Resources



2

2

2


Thesauri



O. Localization9


1,2,3,4,5,6,7,8, 9


4

4

4

O. Aligning

O. Merging

Alignments5

5

5

6

6

6

6

3




RDF(S)OWL


7

O. Design Patterns




1RDF(S)

OWL

FlogicScheduling

NeOn Methodology


Conceptualization:Modular approach for ontology construction

Representation Ontology: WSML

General/Common Ontologies: Time, Geography, Language

Domain O.: Economic Activity, Occupation, Education, Skill, Driving License, Compensation, Labour Regulatory, Competence

ApplicationDomain O. : Job Seeker, Job Offer

-

+

Reusability

-

+Usability


Reference Ontology

LabourRegulatoryOntology

SkillOntology

Language Ontology Occupation

Ontology

Geography Ontology

Time Ontology

EducationOntology

Driving License Ontology

CompensationOntology

EconomicActivity

Ontology

Job OfferOntology

Job SeekerOntology

LE FOREM + BLL + EURES

EURES

ISO 6392

CEFISCO-88 COM

ONET

EURES

ISO 3166

EURES

DAML Time Ontology

FOET

ISCED97

NACE Rev. 1.1

European Legislation

ISO 4217

Ad hoc wrapper

External Sources

has date of birth/ is date of birth of

CompetenceOntology

subClass-Of

subClass-Of


Candidacy

Offered WorkExperience

Objective

ICT Objective

Job Seeker

Vacancy

Organization

Requested Work Experience

ICTVacancy

Job Vacancy

Competence

Education

Language

Contract Type

Compensation

Work Condition

Occupation

Sector

Location

Country

Computing Professionals

has candidacy/belongs to

has objective /belongs to

subClass-Of

has job category

is associated with

subClass-Of

has nationality from /is nation of

resides in /is residence of

has mother language /is mother tongue of

speaks /is spoken by

has competence /is competence of

has education /is education of

has work experience /belongs to

has

wor

k co

nditi

on /

is a

ssoc

iate

d to

ha

s co

ntra

ct t

ype

/is

ass

ocia

ted

to

has

com

pens

atio

n /

is a

ssoc

iate

d to

is

ass

ocia

ted

with

/ha

s lo

catio

n

has activity sector /is associated with


has job category /

is associated with

has job category /

is associated with

has job vacancy/belongs to

has location /is location of

has vacancy/belongs to

subClass-Of

has job category /is associated with

is associated with /requires work experience


has job category/is associated with

requires education /is associated with

requires competence /is associated with

has work condition /is associated with

has contract type /is associated withhas compensation /

is associated with

is located in /is associated with

has job category/is associated with


Job OfferOntology

Job SeekerOntology

OccupationOntology

LanguageOntology

EducationOntology

CompetenceOntology

LabourRegulatoryOntology

CompensationOntology

GeographyOntology

Economic Activity

Ontology

Details of the ontology


Conclusions

1. The NeOn methodology facilitates the reuse and reengineering of non ontological resources into ontologies

2. The reuse of non-ontological resources that have been reached some degree of consensus in a community allows the development of ontologies easier and quicker

asun gomez perez's presentation at sssw 2011

Technology

gmez prez

ontology engineering

engineering asuncin

ontological engineering8

owl ontology

carmen surez figueroa

boris villaznterrazas

building ontologies