A FRAMEWORK FOR MANAGING MULTIPLE ONTOLOGIES:

THE FUNCTION-ORIENTED PERSPECTIVE

Baowen Xu

1, 2

, Peng Wang

, Jianjiang Lu

1, 2, 3

, Dazhou Kang

, Yanhui Li

Department of Computer Science and Engineering, Southeast University, Nanjing 210096, China

Jiangsu Institute of Software Quality, Nanjing 210096, China

PLA University of Science and Technology, Nanjing, 210007, China

Keywords: Semantic Web, Ontology management, Multiple ontologies

Abstract: Ontologies are now ubiquitous in Semantic Web and knowledge representation areas. Managing multiple

ontologies is a challenging issue including comparing existing ontologies, reusing ontologies, maintaining

different versions, and so on. However, most previous multiple ontologies management work focused on

ontologies maintenance, evolutions, and versioning. They ignored the very important point: exploiting the

functions of multiple ontologies provide. This paper proposed a new framework for managing multiple

ontologies based on the function-oriented perspective, and its goal is to bring multiple ontologies together to

provide more powerful capabilities for the practical applications. The new multiple ontologies management

architecture is more feasible and robust in the dynamic and distributed Semantic Web environment.

1 INTRODUCTION

The Semantic Web (Berners-Lee, 2001) envisions a

world-wide distribute architecture where data and

computational resources will easily interoperate

based on semantic marking up of web resources

using ontologies. Ontology is a formal, explicit

specification of a shared conceptualization (Gruber,

1993), and is also the core of knowledge

representation in the Semantic Web. The Semantic

Web researches have improved the popularity of

ontologies greatly. Although large amount of

endeavors have been done for the ontology building

that produced many methodologies, tools and

criteria for helping the ontology development (Noy,

2001, Corcho, 2003, Ding, 2002), we had to accept

the fact that developing ontologies is a labour

intensive work. Today, researchers have already

accepted such a common viewpoint that due to one

cannot expect a single ontology to describe the vast

amounts of data on the web, We believe the

Semantic Web should be built on many small

ontologies (Roussset, 2004, Mena, 2000). We can

easily obtain various ontologies through many ways,

such as from the web ontology library (DAML

Ontology Library) or someone’s papers. Frequently,

using multiple existing ontologies not only can avoid

or reduce the work for building new ontologies, but

also can describing the wider knowledge and satisfying

the requirements of a varied community of users.

Due to the intrinsic syntactic and semantic

heterogeneities between different ontologies,

managing multiple ontologies will face many

challenges and problems (Noy, Musen, et al., 2004,

Ding, 2001, Wendt, 2002). Obviously, we should

develop the ontology maintenance methods

(Stojanovic, 2003) and tools (Noy, 2004) for

multiple ontologies management. Similar to the

single ontology, multiple ontologies’ evolutions and

versioning could be considered in the management

too. However, these aspects are not the ultimate goal

for managing multiple ontologies, and we believe

the real target of managing multiple ontologies is

exploiting their powerful function for the practical

applications. To bring multiple ontologies together,

several ontology management frameworks have

been proposed (Noy, Musen, et al., 2004, Cui, 2000,

Maedche, 2003, Maedche, 2002, Das, 2001).

However, these work focused on the multiple

ontologies maintenance or ontology evolutions. Few

work discussed the methods of managing multiple

ontologies for providing more powerful ability for

the applications such as semantic querying across

multiple ontologies and extracting reasonable sub-

ontologies from the multiple ontologies according

the users’ requirements.

300

Xu B., Wang P., Lu J., Kang D. and Li Y. (2005).

A FRAMEWORK FOR MANAGING MULTIPLE ONTOLOGIES: THE FUNCTION-ORIENTED PERSPECTIVE.

In Proceedings of the Seventh International Conference on Enterprise Information Systems, pages 300-305

DOI: 10.5220/0002538803000305

 SciTePress

This paper presents a new framework to deal

with the multiple ontologies management, and our

idea is based on the multiple ontologies’ functions.

To provide more powerful ability for the practical

applications, we design the five-layer multiple

ontologies management architecture, and investigate

the problems of normalizing multiple ontologies,

expressing the complex relations between ontologies

using bridge ontology, and how to provide functions

for different practical requirements.

The rest of this paper is organized as follows.

Section 2 argues the reasons of using multiple

ontologies, and proposes the multiple ontologies

management tasks we focus here. Section 3 presents

the framework of managing multiple ontologies and

describes the detail of each layer in the framework.

Section 4 discusses the related work of managing

multiple ontologies. Finally, conclusions are

presented in Section 5.

2 MULTIPLE ONTOLOGIES

MANAGEMENT TASKS

In this section, we will discuss the reason of

managing multiple ontologies and argue the

advantages of using multiple ontologies through

comparing the multiple ontologies with single

ontology. Then we analyze the deficiencies of

former multiple ontologies management work and

provide the tasks we want to realize through

managing multiple ontologies.

2.1 Multiple Ontologies Versus Single

Ontology

Why we want to manage multiple ontologies? What

are the advantages of using them? In order to answer

these questions, we begin with the comparison

between single ontology and multiple ontologies

shown as in Table 1. There are seven criterions

listed in the table. First is the knowledge expressive

range. Except for few large-scale ontologies, most

single ontology can only express limited and specific

domain, but the multiple ontologies can express

broader and even the knowledge of crossing

domains. The reasoning range is similar to the first

criterion that multiple ontologies can reason on the

wider range than single ontology could. As far as the

usability, singe ontology is easy to use, but multiple

ontologies are difficult to use for the reason of the

user should know the relations between ontologies in

advance. As for the acquirability, it is not easy to

find a suitable ontology to meet the requirement of

specific domain because each ontology may have

some shortages for represent the knowledge of

current domain, for example it maybe too ‘big’ for

the needs. So in most time, the users have to build a

new one. But it is easy to find multiple ontologies to

overcome this problem, and we just use the suitable

part in each ontology to combine to satisfy the

requirements. The fifth criterion is about the

heterogeneous problem. Single ontology has not this

kind of problem, but it is a serious problem must be

considered in multiple ontologies. How to deal with

the heterogeneity is the key problem in our multiple

ontologies management. As far as the ontology

engineering, single ontology includes building new

ontology or extending the existing ontologies, and

multiple ontology need ontology mapping or

merging. They both are laborious work and lack of

automatic method to support. The last criterion is

flexibility. It is obvious that multiple ontologies are

more flexible than single ontology, and fit the

distributed and dynamic Semantic Web

environment.

From the comparison discussed above, both the

single ontology and the multiple ones have their

advantages and disadvantages. But for the fact that

more and more small ontologies are popular and the

difficulties of building and maintaining big

ontology, it is necessary to face to employ multiple

ontologies. Therefore, we need some feasible

methods to manage multiple ontologies and avoid

their disadvantages.

Table 1: Multiple ontologies versus single ontology

Criterion Single ontology Multiple ontologies

Expressive range Limited and specific domain Wider and cross domain

Reasoning range Narrow Wider

Usability Easy to use Difficult to use

Acquirability

Difficult to find suitable ontology

for specific domain

Easy to find multiple

ontologies for specific domain

Heterogeneity No Yes

Ontology engineering

Building new ontology; Extending

existing ontology

Ontology mapping/alignment

and merging/integration

Flexibility No Yes

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2.2 The Goals of Managing Multiple

Ontologies

There are two main advantages of using multiple

ontologies. First, using multiple ontologies may

realize the ontology reuse. Secondly, the multiple

ontologies are more robust in the dynamic Semantic

Web environment, which is important to the

Semantic Web applications. To achieve these merits,

we need an efficient management to deal with the

problems of using multiple ontologies to reconcile

multiple ontologies. The motivation of this paper is

finding a flexible and low-cost approach to manage

multiple ontologies to meet the tasks of representing

crossing domain knowledge in the dynamic

Semantic Web. Different from the previous work,

we focus on how to exploit the powerful ability of

multiple ontologies provide, and we call this is

function-oriented perspective. The following is some

goals we want to reach.

Query and retrieve across multiple ontologies

Use the mappings defined between ontologies to

support query to one ontology posed in terms of

another ontology. We should manage the useful and

complex relations between ontologies for the

querying rewrite in these applications.

Reason across multiple ontologies Use the

relationships defined between ontologies to support

inference across several ontologies.

Extract sub-ontology from multiple ontologies

Analyze dependencies and allow users to extract sets

of concepts and relations as a sub-ontology.

Interoperability of shared ontologies Specify

transformation rules between different ontologies

and versions of the same ontology; Align and map

between ontologies; Translate ontologies from one

form to another.

3 MULTIPLE ONTOLOGY

MANAGEMENT FRAMEWORK

In this section, we will present the architecture of

managing multiple ontologies. And then we

investigate each functional component in the

framework.

3.1 Architecture

Several frameworks were proposed to manage

multiple ontologies. In the function, these work

mainly focus on the ontology evolution and

maintenance. In the architecture, they just have two-

layer architecture that is ontology repository and

ontology application. There are some disadvantages

in these frameworks. First, the two-layer architecture

is too simple to manage multiple ontologies, and we

need a more systematic architecture. Second, the

functions provide by the multiple ontologies are

embedded in the practical applications, and that

cause many repeated work.

Our idea of solving these problems is based on

two aspects. Firstly, we separate the inter-

relationships among ontologies from multi-

ontologies with bridge ontology, and try to provide

the unified extraction for relationships among

ontologies. After this step, each ontology is still

independent, but we have collected the various

relationships among multiple ontologies. It is a

Figure 1: The architecture of managing multiple ontologies.

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302

flexible way for the dynamic web environment.

Secondly, we separate multi-ontologies functions

from applications to provide unified functions for

practical applications, and also provide substitute

methods for unnecessary ontology engineering work

such as alignment and integration.

Based on these ideas, we design a five-layer

architecture for managing multiple ontologies. The

framework is composed of the ontology base,

ontology representation, bridge ontology to express

the relations between ontologies, unified functions

provided by multiple ontologies, and the practical

applications.

3.2 Ontology Base

We can obtain ontologies from different ways. Each

ontology may be built by different people in

different period, so they may be in different model

and ontology language. Some of them are built in

RDF(S), some are built in OWL. These ontologies

are our source ontologies, and we use the ontology

base to store them.

It is necessary to store all available ontologies in

the ontology base. Choosing ontologies is based on

the users’ requirements. For example, if the users are

interested in university and company, we could only

store many the two kinds of ontologies in the

ontology repository.

3.3 Ontology Representation

There are many different Ontology languages on the

Web, such as OWL, DAML+OIL and Ontolingua.

They are different in syntax and structure, and based

on different logic foundations. Besides the different

in syntax, ontology languages may be based on

different logic system, such as Frame Logic,

Description Logic (DL) and N3. Due to different

representation using different logic model and

language, their expressing abilities are different too.

Therefore, the analyzing, extracting and integrating

methods of them are different. Translating

ontologies into a unified internal representation, i.e.

a unified Ontology model, is necessary.

Generally, an ontology can be seen as a

quadruple O = (C, R, X,

∆

), where ∆ is the set of

individuals; C is the set of concepts, which are

subsets of

∆ ; R is the set of relations, which are

subsets of

∆×∆ ; X is the set of axioms. This

definition is very broad and general. This definition

is too general and is hard to operate the ontologies in

such representation.

In our framework, the information about

individuals is not concerned. We focus on the

concepts and relations. They are both fundamental

elements in most Ontology languages. It makes the

extraction difficult. We consider concepts to be the

only fundamental element, and organize them into a

hierarchy. Relations are divided into attributes

(datatype properties in OWL) and other relations

(object properties in OWL). Attributes are special

relations that between individuals and literals. Both

attributes and relations are depending on the

concepts that they linked; they are not the

fundamental element in Ontology. (The meaning of

these elements in Ontology can be found in OWL

standards of W3C)

Definition 1. We consider an ontology as a

eight-tuple:

O = (C, A

, R, A

, S(C), E(C), H, X)

where C is the set of concepts; A

is the set of

attributes about concept

Cc∈ ; R is the set of

relations; A

is the set of attributes about relation

∈

; S(c) and E(c) are the sets of relations that

can start and end with concept

Cc∈ ; H represents

the concept hierarchy; and X is the set of axioms.

The concept hierarchy is the set of two-tuples of

concepts that have subsumption relations. It

organizes all the concepts into a well-formed

hierarchy.

Relations need to depend on certain concepts.

However, each relation associate to pairs of

concepts; the number of pairs that is the square

number of concepts may be too large to handle. An

alternate plan is to describe the starting and ending

of relations respectively. S(c) is the set of

relations

)}),((|{ rbacaba,Rrr ∈∧

∈

∃

∧

∈

; E(c) is

the set of

relations

)}),((|{ rbacbba,Rrr ∈∧

∈

∃

∧

∈

, where

a, b are individuals. An obvious fact is

that

)()()()(

212121

cEcEcScScc ⊆∧⊆→⊆ ; the

redundancy can be cleared based on this during

implementing.

Attributes are specific relations depending on

only one certain concept or relation; for example,

person name is a string attribute of person. Axioms

are restrictions about the concepts, relations and

attributes. Each axiom is of course depending on the

elements which it put the restrictions.

Visualization of this model is realizable. It can

be viewed as a tree-like concept hierarchy with

concepts as the nodes and relations between the

nodes; attributes are contained in certain concepts

and relations.

This model of Ontology is expressive enough to

represent ontologies in most Ontology languages. It

is possible to translate ontologies in other languages

into this model and vice versa.

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3.4 Bridge Ontology

The multiple ontologies we need are often

overlapped and have relationships between them.

However, we do not expect to involve the

difficulties of ontology integration. The complete

integration will lost the flexibility of multiple

ontologies in the dynamic web. Here, we try to

generate the relations between ontologies to reach

the functions provide by multiple ontologies. We use

a similar but more powerful method to ontology

mapping, and it is bridge ontology (Wang, 2004).

Bridge ontology can describe more refined relations

between ontologies. The bridge ontology is a

peculiar ontology, and has the ability of expressing

the complex relations between multiple ontologies.

It can be created and maintained conveniently, and is

effective in the applications based on multiple

ontologies. In bridge ontology, 12 kinds of relations

between ontologies are presented such as different

between concepts, complex is-a relationships

between concepts, and composed relations between

relations of different ontologies.

First, we generate the relations between

ontologies based on the requirement of applications.

We call these relations as semantic bridges. The

generation process of bridge ontology has semi-

automatic method to support. And all semantic

bridges are managed by bridge ontology. After the

generation of bridge relations, some semantic

redundancies and conflicts could arise. The problem

also can be solved by the algorithms in (Xu, 2004).

After the relations are generated, we just focus

on the management of these relations. Due to the

process of generating relationships is automatic or

semi-automatic, so we can delete ontology or add

new ontology into the current multiple ontologies.

Now, the ontologies in the multiple ontologies are

independent but their inter-relations are extracted.

3.5 Multiple Ontologies Functions

Some functions should be provided by the multiple

ontologies to satisfy the requirements of applications.

Firstly, all semantic bridges in the bridge ontology

could provide simple and complex ontology

mapping and alignment. Secondly, we could merge

many ontologies as a integrated one through the

semantic bridges. Third, for the bridge ontology

generates the relations across ontologies, we can

realize the knowledge inference across multiple

ontologies. And the fourth function is that we can

query across multiple ontologies because the bridge

ontology provide the transform and rewrite of

querying expressions. Finally, through the

interaction with users’ requirement, we can extract

sub-ontology with complete semantic and

independent function from the multiple ontologies

environment (Kang, 2004).

3.6 Expected Applications

Managing multiple ontologies should server for

many practical applications. The semantic

annotation base on multiple ontologies is a typical

application. We use multiple ontologies to provide

more detailed semantic data, and can avoid the

problems of finding fit ontology or building new

ontologies. The information query based multiple

ontologies is also a promising application. Many

semantic search and query involve multiple

ontologies, where the management of multiple

ontologies can provide the precise or approximate

querying transform. Extracting sub-ontology

corresponding to the requirements also is a useful

application.

4 RELATED WORK

Some frameworks of managing multiple ontologies

are proposed (Noy, Musen, et al., 2004, Cui, 2000,

Maedche, 2003, Maedche, 2002). Some research

also put forward some challenges of the ontology

management (Noy, Musen, et al., 2004, Ding, 2001,

Wendt, 2002). Some people deal with the

management of single ontology. (Noy, 2004) use

ontology tool Prompt Pplugin to manage ontology.

(Stojanovic, 2003) discussed the ontology manage

through the modification of an ontology with respect

to user' needs. These previous work give some

foundations for the management of multiple

ontologies. Different people have different

perspective for the ontology management. (Das,

2001) focus on the ontology management in e-

commerce. But we believe that it is a narrow

multiple ontologies management. Some work of

discuss the ontology management focused on the

multiple ontologies evolutions or versioning

problems. They all ignore the most important goal of

managing multiple ontologies that is using multiple

ontologies to realize the more powerful functions

which the single ontology can not provide for.

Therefore, we propose our function-oriented

perspective for managing multiple ontologies. In

other way, managing multiple ontologies is a

promising way to reuse many existing ontologies.

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304

5 CONCLUSIONS

Managing multiple ontologies is a challenging issue.

Most previous work focus on the multiple ontologies

maintenance and evolutions, and ignored the

developing the functions of multiple ontologies. This

paper proposed a new framework for managing

multiple ontologies, and its goal is to bring multiple

ontologies together to provide more powerful

capabilities for the practical applications. The

approach is not only feasible, but also robust in the

dynamic and distributed Semantic Web

environment. Some previous researches provide the

foundations for the feasibility of this framework.

Building a system to realize all ideas in the

framework is the next step work.

ACKNOWLEDGMENTS

This work was supported in part by the Young

Scientist's Fund of NSFC (60373066, 60303024,

60425206, 90412003), National Grand Fundamental

Research 973 Program of China (2002CB312000),

and National Research Foundation for the Doctoral

Program of Higher Education of China

(20020286004).

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