=Paper=
{{Paper
|id=None
|storemode=property
|title=Dynamic is-a Hierarchy Generation for User Centric Semantic Web
|pdfUrl=https://ceur-ws.org/Vol-809/paper-05.pdf
|volume=Vol-809
}}
==Dynamic is-a Hierarchy Generation for User Centric Semantic Web==
https://ceur-ws.org/Vol-809/paper-05.pdf
Dynamic Is-a Hierarchy Generation for User-Centric
Semantic Web
Kouji Kozaki1, Keisuke Hihara1, Riiciro Mizoguchi1
1
The Institute of Scientific and Industrial Research, Osaka University
8-1 Mihogaoka, Ibaraki, Osaka, 567-0047 Japan
{kozaki, hihara, miz}@ei.sanken.osaka-u.ac.jp
Abstract. In ontological theories, is-a hierarchy must represent the essential
property of things and hence should be single-inheritance, since the essential
property of things cannot exist in multiple. However, we cannot avoid multi-
perspective issues when we build an ontology because users often want to
understand things from their own viewpoints. Especially, in the Semantic Web,
the variety of user issues in capturing target domains. In order to tackle this
multi-perspective issue, we should adopt an approach of dynamically
generating is-a hierarchies according to the viewpoints of users from an
ontology using single-inheritance. This article discusses a framework for
dynamic is-a hierarchy generation and its implementation as an extended
function of Hozo. Through the function, users can understand an ontology from
their own viewpoints.
Keywords: ontology, is-a hierarchy generation, viewpoint, multi-perspective
1 Introduction
Ontologies are designed to provide systematized knowledge and machine readable
vocabularies of domains for Semantic Web applications. The competences of
semantic technologies strongly depend on the ontology which they use. Ontology is
defined as “An explicit specification of conceptualization” [1], and it clearly
represents how the target world is captured by people and systems.
Semantics of concepts (classes) are defined clearly through the description of their
relationships between other concepts in an ontology. In particular, the most important
relationship is an is-a (sub-class-of) relationship which represents a relation between a
generalized concept and a specialized concept. Class hierarchies according to is-a
relationships are called is-a hierarchies, and they form the foundation of ontologies.
That is, is-a hierarchies in an ontology reflect how the ontology captures the essential
conceptual structure of the target world.
Therefore, in ontological theories, an is-a hierarchy should be single-inheritance
because the essential property of things cannot exist in multiple. Imagine that objects,
processes, attributes, etc. have their own unique and essential properties. The use of
multiple-inheritance for organizing things necessarily blurs what the essential
property of things is. This observation is strongly supported by the fact that both of
the well-known upper ontologies, DOLCE and BFO, use single-inheritance
hierarchies.
Nicola Guarino criticizes the careless usage of is-a relationships without enough
ontological consideration as is-a overloading [2] and proposes an ontology
development methodology, called OntoClean, which defines concepts based on meta-
properties such as rigidity and anti-rigidity. DOLCE is developed based on the
OntoClean methodology using single-inheritance is-a hierarchy. BFO is the upper
ontology used by the OBO Foundry1 which aims to create a suite of orthogonal
interoperable reference ontologies in the biomedical domain. BFO also uses single-
inheritance hierarchy, and it is recommended in the guidelines of OBO Foundry to
avoid careless usage of multiple-inheritance.
However, we cannot avoid multi-perspective issues when we build an ontology
across multiple domains. It is because domain experts often want to understand the
target world from their own domain-specific viewpoints. In many cases, their interests
are different even if they are experts in the same domain. In some domains, there are
many ways to categorize the same kinds of concepts, and different taxonomies are
used depending on the purpose and situation.
For example, in the medical domain, a disease is interpreted from various
viewpoints. Consider diabetes as an example. Clinician may pay attention to body
parts with the abnormalities and classify diabetes as an abnormal blood sugar level.
On the other hand, certain specialists may pay attention to the main condition and
may classify diabetes as an abnormality in metabolism, and other specialists may
classify diabetes as a lifestyle disease. Staffs administering medical care implicitly
understand which is-a hierarchy should be used for disease interpretation in
correlation with their respective interpretations. This suggests that one is-a hierarchy
of diseases cannot cope with such a diversity of viewpoints since a single-inheritance
hierarchy necessarily represents one viewpoint.
Many efforts are under taken to solve these multi-perspective issues. The OBO
Foundry proposes a guideline for ontology development stating that we should build
only one ontology in each domain [3]. This is an effort to exclude the multi-
perspective nature of domains from ontologies. Ontology mapping is used as an
approach to acceptance of multiple ontologies based on the different perspectives in a
domain. It aims to make clear the relationships between different ontologies.
Someone may consider that multiple-inheritance is an easy way to solve these multi-
perspective issues. Because multiple-inheritance causes some ontological problems as
mentioned above, our ontology development tool, named Hozo2, allows the user to
use a multiple-inheritance only when he/she represents clearly from which upper-
concepts the essential property is inherited3. However, if we define every possible is-a
hierarchy using multiple-inheritances, they would be very verbose and the user’s
viewpoints would become implicit.
In order to tackle these multi-perspective issues, the authors take a user-centric
approach based on ontological viewpoint management. It dynamically generates is-a
hierarchies according to the viewpoint of users from an ontology using single-
1 http://www.obofoundry.org/
2 http://www.hozo.jp
3 It is represented by two kinds of is-a relationships: (essential) is-a and (non-essential) IS-A.
inheritance. The main strategy is composed of: (1) fixing the conceptual structure of
an ontology using single-inheritance based on ontological theories and (2)
reorganizing some conceptual structures from the ontology on the fly as visualizations
to cope with various viewpoints. Based on this strategy, the authors consider a
framework for dynamic is-a hierarchy generation according to the interests of the user
and implement the framework as an extended function of the ontology development
tool Hozo [4]. In this article, we discuss the framework for dynamic is-a hierarchy
generation and its application to a medical ontology. It would solve the conflicting
requirements of multi-perspective and single-inheritance in a good ontology, and it
could contribute to a user-centric Semantic Web.
The rest of this paper is organized as follows: In section 2, we introduce dynamic
is-a hierarchy generation according to viewpoints. In section 3, we discuss
implementation of the framework as an additional function of Hozo. In section 4, we
shows its application to a medical ontology for dynamic is-a hierarchy generation of
disease. In section 5, we discuss related work. Finally, we present concluding remarks
with future work.
2 Dynamic Is-a Hierarchy Generation according to Viewpoints
2.1 Ontology Representation in Hozo
We implement the dynamic is-a hierarchy generation system as an additional function
of Hozo [4]. Fig.1 shows an example of ontology defined using Hozo. Ontologies are
represented by nodes, slots and links. The nodes represent concepts (classes), is-a
links represent is-a (subclass-of) relations, and slots represents part-of (denoted by
“p/o”) or attribute-of (denoted by “a/o”) relations. A slot consists of its kind (“p/o” or
“a/o”), role concept, class restriction, cardinality. Roughly speaking, a slot
corresponds to property in OWL and its role name represent name of property. Its
Is‐a link represents Node represents a concept
an is‐a relation (=rdfs:Class)
(=rdfs:subClassOf)
Refer to
Role concept
(≒property name )
Refer to
Class restriction
(=owl:someValuesFrom )
cardinality
(=owl:cardinality)
p/o slot represents
a part‐of relation
(=rdf:Property)
a/o slot represents an
attribute‐of relation
(=rdf:Property)
Fig.1 An example of ontology defined using Hozo.
class restriction and cardinality correspond to owl:someValuesFrom and
owl:cardinality respectively. Their restrictions refer to other concepts which are
defined elsewhere. However, semantics of Hozo’s ontology includes some concepts
related to role which are not supported in OWL because it is designed based on an
ontological theory of role [5]. While we have designed three levels of role
representation model in OWL to capture the semantics level-wise [6], we use the
simplest model described above in this paper.
In the target ontologies, concepts (classes) are defined by several slots which
represent properties and restrictions for them. These definitions are inherited from
super-concepts (super-classes) to their sub-concepts (sub-classes) along with is-a
links. Furthermore, in some sub-concepts, some inherited definitions are specialized
according to is-a hierarchies of concepts which are referred by their restrictions. For
example, bicycle in Fig.1 inherits front-wheel from Two-wheeled vehicle and its class-
restriction could be specialized from Wheel to Bicycle-wheel. This research focuses
on these characteristics of is-a hierarchies and considers an approach to reorganize is-
a hierarchies of concepts based on is-a hierarchies of concepts referred to by their
definitions.
2.2 Dynamic Is-a Hierarchy Generation through Transcription of a Hierarchical
Structure
Fig.2 outlines a framework for dynamic is-a generation. It generates is-a hierarchies
by reorganizing the conceptual structures of the target concepts selected by a user
based on the user’s viewpoint. The viewpoint is represented by an aspect and a base
hierarchy. By aspect, we mean something which the user is interested in and selects
from the definition of the target concept to generate an is-a hierarchy. By base
hierarchy, we mean a conceptual structure of concepts which are referred to by the
definition selected as the aspect. Because sub-concepts of the target concept could be
defined by specializing their inherited definitions according to the base hierarchy, we
could reorganize the is-a hierarchy of the target concepts according to the following
steps:
Reorganization (4)
X Target concept Transcriptional
X hierarchy
Original
is-a hierarchy
(1) (3) Generated is-a hierarchy
Aspect
Transcription of a base
refer to hierarchical stricture
Definition of the
target concept
A A A
Viewpoint
Generated
Is-a hierarchy P-is-a hierarchy is-a hierarchy
Base hierarchy
(2)
Fig.2 A framework for dynamic is-a generation.
Step 1: Selection of an aspect
The user selects something as an aspect from the definition of the target concept for
dynamic is-a hierarchy generation (see. Fig.2(1)). Because any concept is defined in
terms of slots each of which consists of a role-concept, a role-holder [5] and a class-
restriction, he/she can select one of them as an aspect. In this paper, we consider only
a case where the user selects a class restriction as an aspect for simplicity.
Step 2: Selection of a base hierarchy
The user selects a base hierarchy from hierarchies of concepts which the aspect is
referring to (see. Fig.2(2)). In Hozo, three kinds of conceptual hierarchies could be the
base hierarchy as follows: the is-a hierarchy of concepts referred to by the aspect, the
p-is-a hierarchy generated by the system according to part-whole relationships of the
concepts referred to, and dynamically generated is-a hierarchies using the proposed
method. A p-is-a hierarchy is obtained by abstracting parts from a part-of hierarchy
[7]. The detail of the p-is-a hierarchy is discussed in section 2.3.2.
Step 3: Transcription of a hierarchical structure
The system defines new sub-concepts of the top concept of target concepts by
specializing the definition of the top concept according to the class restriction
selected as an aspect and base hierarchy (see. Fig.2(3)). Then, their concept names are
automatically determined by the system using a template such as “ with as ”. As a result,
an is-a hierarchy which has the same conceptual structure with the base hierarchy is
generated. We call the generated hierarchy a transcriptional hierarchy and the
operations to generate it a transcription of a hierarchical structure.
The scope of a transcription of the base hierarchy could be managed by specifying
the number of the target layers rather than to use all concepts of the base hierarchy for
transcription.
Step 4: Reorganization of is-a hierarchy based on a transcriptional hierarchy
The system reorganizes the is-a hierarchy by comparing the original is-a hierarchy
and the transcriptional hierarchy generated in step 3. The system compares the sub-
concepts of the target concept (we call them existing sub-concepts) with the concepts
on the transcriptional hierarchy (we call them generated sub-concepts) according to
the aspect and the base hierarchy. When an existing sub-concept’s definition specified
by the aspect subsumes the definition of a generated sub-concept, the existing sub-
concept is classified into sub-concepts of the generated sub-concept. If an existing
concept is classified into sub-concepts of multiple generated sub-concepts, the
existing concept is classified into the lowest sub-concepts. As a result, all existing
concepts are classified into sub-concepts of the generated concepts on the
transcriptional hierarchy according to the aspect and the base hierarchy4.
Through the above four steps, the system can dynamically generate is-a hierarchies by
reorganizing existing sub-concepts according to the transcriptional hierarchies of base
hierarchies.
4 The result of reorganization corresponds to the result of classification using DL-reasoner
while it is implemented by procedural ways in Hozo.
Original is-a hierarchy of “disease”
The aspect (1) disease
(3) The transcriptional
hierarchy
Refer to
Angina Myocardial Stroke diabetes heart disease
infarction
(5)
Classification into sub‐concepts
of generated sub‐concepts (4)
type1 diabetes type2 diabetes
The legend
abnormal state
(2) Is‐a relationships defined in the original ontology
The base hierarchy vessel abnormality blood abnormality Is‐a relationships generated in the transcription
(is-a hierarchy of of the base hierarchy
“abnormal states”) stenosis infarction hyperglycemia
Is‐a relationships generated in the reorganization
of is‐a hierarchy
Fig.3 An example of dynamic is-a generation of disease in the case that is-a hierarchy
of abnormal state is selected as the base hierarchy.
Although DL-reasoners can classify classes (concepts) automatically by reasoning,
the result of classification is only an is-a hierarchy which is determined uniquely
according to the definitions of the classes. Therefore, it is different from our dynamic
reorganization according to the users’ viewpoints. DL-reasoners can generate a
different is-a hierarchy only when class definitions in the ontology have changed.
2.3 Examples of Dynamic Is-a Generations
§１ In the Case of that an Is-a Hierarchy is Selected as a Base Hierarchy
As an example, we consider a dynamic is-a generation of diseases which is defined in
terms of several slots such as “main pathological state”, “abnormal object” and so on
(see. Fig.3). Here, we suppose the user selects the class-restriction of “main
pathological state” as an aspect (Fig.3(1)) and the is-a hierarchy of “abnormal state”
as a base hierarchy (Fig.3(2)).
First, sub-concepts of “disease” such as “disease with vessel abnormality as main
pathological state” and “disease with blood abnormality as main pathological state”
are dynamically generated by specializing the definition of “disease” according to the
class restriction selected as the aspect and the base hierarchy. After repetitions of
generations of sub-concepts, the transcriptional hierarchy of “disease” is obtained
(Fig.3(3)). Then, existing sub-concepts of “disease”, such as “myocardial infarction”
and “angina pectoris” are classified into sub-concepts of generated sub-concepts on
the transcriptional hierarchy through comparisons between definitions of them
(Fig.3(4)). When more than one existing sub-concepts are classified into the same
generated sub-concept, they could be organized based on the original is-a
Original is-a hierarchy of “disease”
(3) disease
The transcriptional
hierarchy
The aspect
(1)
diabetes heart disease
Stroke
(4) type1 diabetes type2 diabetes Angina Myocardial
Classification into sub‐concepts infarction
of generated sub‐concepts
p‐human body The legend
Is‐a relationships defined in the
p‐nervous p‐circulatory original ontology
The base hierarchy system system
Is‐a relationships generated in the
（p‐is‐a hierarchy of p‐brain p‐heart p‐blood transcription of the base hierarchy
“human body”）
Is‐a relationships generated in the
(2) reorganization of is‐a hierarchy
Fig.4 An example of dynamic is-a generation of disease in the case that p-is-a
hierarchy of human body is selected as the base hierarchy.
relationships between them. In the case shown in Fig.3(5), because is-a relationships
between “disease with hyperglycemia as main pathological state” and “type1/type2
diabetes” can be identified by reasoning, “type1/type2 diabetes” are classified into
sub-concepts of diabetes according to the original is-a relationships.
§２ In the Case of that an p-is-a Hierarchy is Selected as a Base Hierarchy
In the next example, we suppose the user selects the class-restriction of “abnormal
object” as the aspect and the p-is-a hierarchy of “human body” as the base hierarchy
for a dynamic is-a generation of disease in the same ontology with the previous
example (Fig.4(1),(2)).
In the property inheritance mechanism of ordinary is-a relationship, when a super-
class and its sub-class have the same slot, the class restriction of the sub-class’s slot
must be a sub-class of the super-class’s one as well. However, in some case, the class
restriction of the sub-class’s slot must be a part of the super-class’s. For example,
when , both “disease of a
pulmonary valve” and “disease of a heart” have a slot of “site of the disease” and the
class restriction of the former must be a part of the latter, that is .
To cope with such cases, on
the basis of our latest theory of
roles, we introduced “p-” operator
in Hozo which automatically We write “p-heart”
generates a generic concept instead of “heart”．
representing all the parts of the
entity to which the operator is
attached. The operator enables
parts to be inherited by ordinary Fig.5 An example of usage of p-operator.
property inheritance mechanism. In the case of Fig.5, for example, we write “p-heart”
instead of “heart”, then the slot of its subclass inherits not subclass of “heart” but its
parts. When p-X is used, Hozo automatically generates a generic concept representing
all of the defined parts of X including all parts which have X as their ancestor. This is
valid because each part is a subclass of “X’s parts class” which coincides with p-X.
According to mereology, the theory of parts, p-X includes itself which is not the very
X as an entity but X as its part.
On the basis of this theory, Hozo automatically generates is-a relationships
between p-X such as . As a result, an is-a hierarchy
of p-X is generated according to part-of hierarchy of X. The is-a hierarchy of p-X is
called p-is-a hierarchy5 and could be selected as a base hierarchy for a dynamic is-a
generation.
In the case of Fig.4, since the class restriction of “abnormal object” is “p-human
body”, we can select it as an aspect and p-is-a hierarchy as a base hierarchy for
dynamic is-a generation. Then, sub-concepts of “disease” such as “disease with p-
nervous system as abnormal object” and “disease with p-circulatory system as
abnormal object” are dynamically generated according to the aspect and the base
hierarchy. As a result, the transcriptional hierarchy of “disease” based on p-is-a
hierarchy of “p-human body” is obtained (Fig.4(3)). The existing sub-concepts of
“disease” are classified into the transcriptional hierarchy like Fig.4(4).
In addition to these examples, we can select is-a hierarchies which are generated
using the proposed method as a base hierarchy to generate another is-a hierarchies.
That is, our dynamic is-a generation could be executed recursively.
The dynamic is-a generation is applicable to reorganizations of a portion of an is-a
hierarchy of “disease”. For example, we can select a middle-level concept (e.g.
“disease of heart” as the target concept for the dynamic is-a generation.
In these ways, we can dynamically generate is-a hierarchies of diseases according
to the selected aspects and base is-a hierarchies from various viewpoints.
3. Implementation
We implemented a prototype of dynamic is-a hierarchy generation system as an
extended function of Hozo. The system was developed using HozoCore, which is
Java API for ontologies built using Hozo, and Hozo OAT (Ontology Application
Toolkit), which is Java library for GUI of ontology-based applications developed
using HozoCore.
The new function consists of three modules: is-a hierarchy viewer, viewpoint
setting dialog, and dynamic is-a generation module. The is-a hierarchy viewer shows
an is-a hierarchy of an ontology in a tree representation (Fig.6). The user selects a
target concept on the is-a hierarchy for a dynamic is-a generation. The definition of
the selected target concept is shown on the viewpoint setting dialog. In the dialog, the
user selects a viewpoint for the dynamic is-a generation by choosing an aspect, a kind
5 To deal with p-is-a hierarchies in OWL, we can represent them by some design pattern of
ontologies such as SEP triple proposed by Udo Hahn and his group [8].
Hozo ontology
Hozo‐ontology editor
HozoCore
OWL ontology
Is‐a hierarchy viewer Viewpoint setting dialog
Dynamic is‐a hierarchy generation module
Fig.6 The architecture of the dynamic is-a hierarchy generation system.
of base hierarchy and the number of target layers of a transcriptional hierarchy
according to his/her interests. The dynamic is-a generation module generates an is-a
hierarchy according to the specified viewpoint. The generated is-a hierarchy is shown
on the is-a hierarchy viewer and could be saved as an ontology file.
While the target of the system is an ontology in Hozo’s format, it also can support
an ontology in OWL because Hozo can import/export OWL ontologies. When the
generated is-a hierarchy is exported in the OWL format, its generated sub-concepts in
the transcriptional hierarchy are represented by owl:equivalentClass which have
restriction on properties selected as the aspect. The user can reorganize the is-a
hierarchy of the exported OWL ontology based on the transcriptional hierarchy by
reasoning using a DL reasoner.
5. Application of Dynamic Is-a Generation to a Medical Ontology
We applied dynamic is-a hierarchy generation system to a medical ontology which
we are developing in a project supported by Japanese government [7, 9]. In our
medical ontology, diseases are defined by specifying typical disorder roles, such as
pathological condition, symptom, played by abnormal state. Fig.7(a) shows the
framework to define diseases. Its disorder roles are represented as slots with class-
restrictions for constraining slot values. These slots are used as aspects for dynamic
generation of is-a hierarchies of diseases.
For example, when we select the pathological condition of disease as an aspect and
the is-a hierarchy of abnormal state as the base hierarchy, the is-a hierarchy of disease
is generated (Fig.7(c)). In the generated is-a hierarchy, concepts which have names
represented by “disease which has X as pathological condition” (e.g. disease which
has abnormality in the structure as pathological condition) are sub-concepts
generated through the dynamic is-a hierarchy generation. Their concept names are
automatically determined by the system using a template. Exiting sub-concepts are
reorganized as sub-concepts of them. For instance, acute cardiac infarction is
classified into a sub-concept of disease which has cardiac infarction as pathological
condition. From the generated is-a hierarchy, we can understand diseases according to
the classification of pathological conditions.
(a) The framework to define diseases. (b) The class-restriction selected as an aspect.
The original is-a hierarchy of “disease”
The generated is-a hierarchy
(c) The generated is-a hierarchy.
Fig.7 Application of dynamic is-a generation to a medical ontology.
On the other hand, when we select the object of pathological condition as an aspect
and p-is-a hierarchy of the human body as a base hierarchy, the system generates the
is-a hierarchy of disease which is similar to the part-whole hierarchy of the human
body. For instance, acute cardiac infarction is classified into a sub-concepts of
disease which has a pathological condition in the myocardium.
Moreover, we have developed a medical information system to consider how the
dynamic is-a hierarchy generation function can be used in other systems [10]. It is
used as an index for semantic navigation in the system. We also performed an
informal evaluation of the implemented system in a workshop 6 and received
6 The number of participants was about 25. It includes not only the members of the medical
ontology development but also others who work in the medical domain.
favorable comments from medical experts. They especially liked the dynamic is-a
hierarchy reorganization, which is the first solution to the multi-perspective issues of
medical knowledge in the world.
5. Related Work
In order to avoid multiple-inheritance, some researchers took an approach that they
developed ontologies using single-inheritance and reorganized them by reasoning
using a DL-reasoner [11]. It corresponds to reorganization of is-a hierarchy based on
a transcriptional hierarchy in step 4 of the proposed method. However, the approach
needs that the transcriptional hierarchy is developed in advance while it is
dynamically generated by the system in the case of the proposed method.
Faceted Classification is used to represent classifications from multiple-
perspectives. In the Semantic Web, some researchers proposed Faceted Search for
semantic portals [12, 13]. They use Faceted Classification according to the user’s
choose of facets from the definition of ontologies to provide user-centric semantic
search. In order to formalize the Faceted Classification, Bene Rodriguez-Castro
proposed an ontology design pattern to represent Faceted Classification in OWL [14].
Although the proposed method use a similar technique to Faceted Classification for
transcription of a hierarchical structure, it is different from Faceted Classification
since we focus on considerations of ontological meaning of generated is-a hierarchies.
Introduction of a p-is-a hierarchy is one of the results of the ontological investigations.
However, there are some rooms to ontological investigate on a method of dynamic
is-a hierarchy generation. For instance, we need to investigate is-a hierarchies of role-
concepts and role-holders [5] while this paper concentrated on is-a hierarchies of
basic concept (normal type). Dynamic is-a hierarchy generation based on more
complicated viewpoints is also important subject to be considered. For example, we
are considering viewpoints to cope with a new disease model based on an ontological
consideration of causal chains [9]. Because the latest version of our medical ontology
based on the new disease model has more rich definitions than previous one, it would
support more complicated viewpoints for dynamic is-a hierarchy generation based on
causal chains in diseases. We believe these ontological considerations would clarify
the feature of the proposed method.
6. Concluding Remarks
In this paper, we discussed multi-perspective issues of is-a hierarchy construction
in ontologies and proposed a method of dynamic generation of is-a hierarchies. The
main idea is reorganization of is-a hierarchies from the original ontology according to
viewpoints of users. The proposed method was implemented as a new function of
Hozo, and we applied it to our medical ontology for a preliminary evaluation. As a
result, we confirmed that it could generate several kinds of is-a hierarchies from the
medical ontology according to the user’s viewpoints. As of April 12, 2011, 6051
diseases have been defined in the medical ontology by 12 clinicians, and these
definitions are currently being refined. The demonstration of the dynamic is-a
hierarchy generation is available at http://www.hozo.jp/demo/. The function is also
supported by the latest version of Hozo.
Currently, we are improving the dynamic is-a hierarchy generation function in
order to support more detailed disease model which we proposed in [9]. We are also
developing a dynamic is-a hierarchy generation system for OWL ontologies using
OWL-API while it is partly available through OWL import/export function of Hozo.
Future work includes ontological investigations of the proposed method and
evaluation of the system through application of several ontologies.
Acknowledgement
A part of this research is supported by the Ministry of Health, Labour and Welfare,
Japan, the Japan Society for the Promotion of Science (JSPS) through its “Funding
Program for World-Leading Innovative R&D on Science and Technology (FIRST
Program)”, and Grant-in-Aid for Young Scientists (A) 20680009.
References
1. Gruber,T.: A translation approach to portable ontology specifications, Proc. of
JKAW'92:89-108 (1992)
2. Guarino, N: Some Ontological Principles for Designing Upper Level Lexical Resources,
Proc. of International Conference on Lexical Resources and Evaluation (1998)
3. Smith, B. et al.:The OBO Foundry: coordinated evolution of ontologies to support
biomedical data integration, Nature Biotechnology, 25(11):1251-1255 (2007)
4. Kozaki, K. et al.: Hozo: An Environment for Building/Using Ontologies Based on a
Fundamental Consideration of "Role" and "Relationship", Proc. of EKAW2002,LNCS
2473:213-218 (2002)
5. Mizoguchi, R. et al.: A Model of Roles within an Ontology Development Tool: Hozo, J. of
Applied Ontology, 2(2):159-179 (2007)
6. Kozaki, K., et.al.: Role Representation Model Using OWL and SWRL, In Proc. of 2nd
Workshop on Roles and Relationships in Object Oriented Programming, Multiagent
Systems, and Ontologies, Berlin, July 30-31, (2007)
7. Mizoguchi, R. et al.: An Advanced Clinical Ontology, Proc. of ICBO:119-122 (2009)
8. Hahn U, et al.: Turning Lead into Gold?, Proc. of EKAW2002, LNCS 2473:182-196 (2002)
9. Mizoguchi, R. et al.: River Flow Model of Diseases, Proc. of ICBO2011: 63-70 (2011)
10. Kou, H., Ohta, M. Zhou, J., Kozaki, K., Mizoguchi, R., Imai, T., and Ohe, K.: Development
of Fundamental Technologies for Better Understanding of Clinical Medical Ontologies,
Proc. of KEOD 2010:235-240, Valencia, Spain, October 25-28 (2010)
11. Nico Adams, Edward O. Cannon, Peter Murray-Rust: ChemAxiom -An Ontological
Framework for Chemistry in Science, Proc. of ICBO:15-18 (2009)
12. Osma Suominen, Kim Viljanen, and Eero Hyvönen: User-centric Faceted Search for
Semantic Portals, Proc. of ESWC2007, LNCS 4519 :356-370 (2007)
13. Markus Holi: Crisp, Fuzzy, and Probabilistic Faceted Semantic Search, PhD Thesis, Aalto
University, Finland (2010)
14. Bene Rodriguez-Castro, Hugh Glaser, and Les Carr: How to Reuse a Faceted Classification
and Put it on the Semantic Web, Proc. of ISWC2010, LNCS 6496:663–678 (2010)