This pattern for re-engineering non-ontological resources (pr-nor) ﬁts in the schema re-engineering category proposed by [3]. The pattern deﬁnes a procedure that transforms the classiﬁcation scheme components into ontology representational primitives. This pattern comes from the experience of ontology engineers in developing ontologies using classiﬁcation schemes in several projects (seemp 1 , neon 2 , and knowledge web 3 ). The pattern is included in a pool of patterns, which is a key element of our method for re-engineering non-ontological resources into ontologies [2]. The patterns generate the ontologies at a conceptualization level, independent of the ontology implementation language

Gómez-Pérez, A.

Suárez-Figueroa, Mari Carmen

Villazón-Terrazas, B.

English

Archivo Digital UPM

G´ omez-P´ e r e z ,J .L e h m a n n

ı a ,A .G ´ omez-P´ e r e z

NeOn Deliverable D2.5.1. A Library of Ontology Design Patterns: reusable solutions for collaborative design of networked ontologies.

Recursive database structures.

Pattern for Re-engineering a Classification Scheme, which Follows the Adjacency List Data Model, to a

Taxonomy

Servicio de Coordinación de Bibliotecas de la Universidad Politécnica de Madrid

Pattern for Re-engineering a Classiﬁcation
Scheme, Which Follows the Adjacency List Data
Model, to a Taxonomy
http://ontologydesignpatterns.org/wiki/Submissions:Classiﬁcation scheme -
adjacency list model - to Taxonomy
Boris Villazo´n-Terrazas1, Mari Carmen Sua´rez-Figueroa1, and Asuncio´n
Go´mez-Pe´rez1
Ontology Engineering Group, Departamento de Inteligencia Artiﬁcial, Facultad de
Informa´tica, Universidad Polite´cnica de Madrid, Spain
{bvillazon,mcsuarez,asun}@fi.upm.es,
WWW home page: http://www.oeg-upm.net/
1 Introduction
This pattern for re-engineering non-ontological resources (PR-NOR) ﬁts in the
Schema Re-engineering Category proposed by [3]. The pattern deﬁnes a proce-
dure that transforms the classiﬁcation scheme components into ontology repre-
sentational primitives. This pattern comes from the experience of ontology en-
gineers in developing ontologies using classiﬁcation schemes in several projects
(SEEMP1, NeOn2, and Knowledge Web3). The pattern is included in a pool of
patterns, which is a key element of our method for re-engineering non-ontological
resources into ontologies [2]. The patterns generate the ontologies at a concep-
tualization level, independent of the ontology implementation language.
2 Pattern
Problem
Re-engineering a classiﬁcation scheme, which follows the adjacency list model, to design a
taxonomy.
Non-Ontological Resource
A non-ontological resource holds a classiﬁcation
scheme which follows the adjacency list model. A
classiﬁcation scheme is a rooted tree of concepts,
in which each concept groups entities by some par-
ticular degree of similarity.
The semantics of the hierarchical relation between
parents and children concepts may vary depending
of the context. The adjacency list data model [1]
for hierarchical classiﬁcations proposes to create
an entity which holds a list of items with a linking
column associated to their parent items.
1
http://www.seemp.org
2
http://www.neon-project.org
3
http://knowledgeweb.semanticweb.org
116
Applicability
The semantics of the relation between parent and children items are subClassOf.
There is not multi-inheritance nor cyclic relations.
Ontology Generated
The ontology generated will be based on the tax-
onomy architectural pattern (AP-TX-01) [4].
Each category in the classiﬁcation scheme is
mapped to a class, and the semantics of the re-
lationship between children and parent categories
are mapped to subClassOf relations.
Process - Solution
1. Identify the classiﬁcation scheme items which
do not have a parent key value, i.e. classiﬁca-
tion scheme items without parents.
2. For each one of the above identiﬁed classiﬁ-
cation scheme items cei:
2.1. Create the corresponding ontology class,
Ci class.
2.2. Identify the classiﬁcation scheme items,
cej , which are children of cei, by using
the parent key values.
2.3. For each one of the above identiﬁed clas-
siﬁcation scheme items cej :
2.3.1. Create the corresponding ontology
class, Cj class.
2.3.2. Set up the subClassOf relation be-
tween Cj and Ci.
2.3.3. Repeat from step 2.2 for cej as a
new cei.
3. If there are more than one classiﬁcation
scheme items without parent cei
3.1. Create an ad-hoc class as the root class
of the ontology.
3.2. Set up the subClassOf relation between
Ci class and the root class.
Example
Suppose that someone wants to build an ontology based on the water areas classiﬁcation published
by FAO. This classiﬁcation scheme follows the adjacency list data model.
Non-Ontological Resource
The FAO classiﬁcation for water areas groups
them according to some diﬀerent criteria as envi-
ronment, statistics, and jurisdiction, among oth-
ers. This classiﬁcation scheme is available at
http://www.fao.org/ﬁgis/servlet/RefServlet
117
Ontology Generated
The ontology generated will be based on the tax-
onomy architectural pattern (AP-TX-01) [4].
Each category in the classiﬁcation scheme is
mapped to a class, and the semantics of the re-
lationship between children and parent categories
are mapped to subClassOf relations.
Process - Solution
1. Create the Water area class.
2. Create the Environmental area class, and set
up the subClassOf relation between the
Environmental area class and the Water area
class.
2.1. Create the Inland/marine class, and
set up the subClassOf relation be-
tween the Inland/marine class and the
Environmental area class.
2.2. Create the Ocean class, and set up the
subClassOf relation between the Ocean
class and the Environmental area class.
2.3. Create the North/South/Equatorial
class, and set up the sub-
ClassOf relation between the
North/South/Equatorial class and
the Environmental area class.
3. Create the Fishing Statistical area class,
and set up the subClassOf relation between
the Fishing Statistical area class and the
Water area class.
3.1. Create the FAO statistical area class,
and set up the subClassOf relation
between the FAO statistical area class
and the Fishing Statistical area class.
3.2. Create the Areal grid system class, and
set up the subClassOf relation be-
tween the Areal grid system class and
the Fishing Statistical area class.
4. Create the Jurisdiction area class, and set
up the subClassOf relation between the
Jurisdiction area class and the Water area
class.
Related Resources
This pattern is related to the architectural pattern TX-AP-01 [4] for modelling a taxonomy.
3 Pattern Usage
This pattern was applied to re-engineer the ISTAT4, geography italian stan-
dard, into a Geography Ontology5, within the context of the SEEMP project.
This standard is a classiﬁcation scheme which consists of 4 divisions, 20 regions
and 106 provinces. ISTAT is modelled following the adjacency list data model.
Because of the number of divisions, regions and provinces of the ISTAT standard,
it was not practical to create the ontology manually. Therefore, we created an
4 http://www.istat.it/
5 The ontology is available at http://droz.dia.ﬁ.upm.es/hrmontology/
118
ad-hoc wrapper, implemented in Java, that reads the data from the resource im-
plementation and automatically creates the corresponding elements of the new
ontology following the suggestion given by the pattern.
4 Summary and Future Work
We have presented a pattern for transforming a classiﬁcation scheme, which is
modelled following the adjacency list data model, into a taxonomy. The pattern
is included in a pool of patterns, which is a key element of our method for
re-engineering non-ontological resources into ontologies [2].
We plan to develop software libraries within a framework that implement the
transformation process suggested by the pattern. Moreover, we will include exter-
nal resources to improve the quality of the resultant ontologies. Finally, we need
to calculate how much eﬀort do we save re-engineering classiﬁcation schemes us-
ing patterns compared with re-engineering classiﬁcation schemes without them.
Acknowledgments. This work has been partially supported by the European
Comission projects NeOn(FP6-027595) and SEEMP(FP6-027347), as well as by
an R+D grant from the UPM.
References
1. D. Brandon. Recursive database structures. Journal of Computing Sciences in
Colleges, 2005.
2. A. Garc´ıa, A. Go´mez-Pe´rez, M. C. Sua´rez-Figueroa, and B. Villazo´n-Terrazas. A
Pattern Based Approach for Re-engineering Non-Ontological Resources into On-
tologies. In Proceedings of the 3rd Asian Semantic Web Conference (ASWC2008).
Springer-Verlag, 2008.
3. V. Presutti, A. Gangemi, S. David, G. Aguado de Cea, M. C. Surez-Figueroa,
E. Montiel-Ponsoda, and M. Poveda. NeOn Deliverable D2.5.1. A Library of On-
tology Design Patterns: reusable solutions for collaborative design of networked
ontologies. In NeOn Project. http://www.neon-project.org, 2008.
4. M. C. Sua´rez-Figueroa, S. Brockmans, A. Gangemi, A. Go´mez-Pe´rez, J. Lehmann,
H. Lewen, V. Presutti, and M. Sabou. Neon modelling components. Technical
report, NeOn project deliverable D5.1.1, 2007.
119


http://oa.upm.es/5041/1/PattforRe-engineTerm-basedThesaurus%2Cwhichfollows_the_adjacencyList_data_model%2C_to_a_taxonomy.pdf

Pattern for Re-engineering a Classification Scheme, which Follows the Adjacency List Data Model, to a Taxonomy

Abstract

Similar works

Full text

Available Versions

Archivo Digital UPM

Servicio de Coordinación de Bibliotecas de la Universidad Politécnica de Madrid