Ontology Library

A New Approach for Storing, Searching and Discovering Ontologies

Daniel Kotowski and Deborah A. Stacey

School of Computer Science, University of Guelph, 50 Stone Rd. E., Guelph, Canada

Keywords:

Ontology, Ontology Reuse, Ontology Repository, Ontology Library, Knowledge Sharing, Knowledge

Engineering.

Abstract:

The backbone of semantic web technologies is the ontology. This is a powerful structure, which allows for the

capture, reasoning and storing of expert knowledge across various domains. Ideally these structures should be

developed and implemented by experts in a set domain as well as designed with re-usability in mind. However,

often due to the lack of availability and difﬁculties of discovering ontologies, these structures are repeatedly

recreated. Current methods for storing, discovering and sharing ontologies employ similar techniques as to

those used for software source code or static web pages. These are exposed to the limitation inherent with

keyword-based searches, such as ambiguity with the keywords themselves and therefore, the most relevant

ontology may not be discovered. This paper will examine some of the existing techniques used for the storing

and sharing of ontologies. It will offer a contrasting method analogous to software libraries to develop a

standard to store, share, discover, and distribute common ontologies.

1 INTRODUCTION

The applicability of ontologies stretches across sev-

eral domains. Ontologies not only describe but also

reason across data which is a powerful tool for de-

velopers and data mining. However, these structures

perform a complex task and are inherently complex to

produce, validate, discover, and distribute. Although

it may not be possible to decrease the difﬁculty of cre-

ation and validation of these knowledge artefacts, it is

possible to decrease the complexity of the discovery

and distribution of ontologies.

Although the semantic web initiative has helped

bolster the use of this technology, it has yet to provide

a solution for easy search and distribution of ontolo-

gies. This is crucial for ontologies to reach critical

mass. Considering the cost of entry and difﬁculty of

designing and validating an ontology most users may

not choose to use them. To reduce the cost of en-

try substantially, ontologies need a tool to make them

complete, validated, reputable and of high availabil-

ity.

In this paper we will examine, several existing on-

tology repository projects with emphasis on discov-

ery, reuse and distribution of ontologies for an average

user. We will also deﬁne for whom we are design-

ing this library (user-centred design). When examin-

ing the existing ontology repositories we will exam-

ine them against the deﬁned general user and the key

factors they are looking for.

This paper will look at repositories which specif-

ically focus on the discovery and distribution of on-

tologies. What are the key gaps that exist. As well we

will purpose a method analogous to software libraries

and describe why this metaphor works so well with

ontologies.

2 ONTOLOGIES, THEIR DESIGN

AND THEIR USERS

In this section we will examine what ontologies are

and how they are developed. This will give us context

for these structures and their unique properties along

with insight as to how to actually distribute them.

2.1 Ontologies and Ontology

Engineering

Ontologies are deﬁned as “a formal, explicit speci-

ﬁcation of a shared conceptualization. Conceptual-

ization refers to an abstract model of phenomena in

the world by having identiﬁed the relevant concepts

271

Kotowski D. and A. Stacey D..

Ontology Library - A New Approach for Storing, Searching and Discovering Ontologies.

DOI: 10.5220/0004145702710277

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2012), pages 271-277

ISBN: 978-989-8565-30-3

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

of those phenomena. Explicit means that the type of

concepts used, and the constraints on their use are ex-

plicitly deﬁned. Formal refers to the fact that the on-

tology should be machine readable. Shared reﬂects

that ontology should capture consensual knowledge

accepted by the communities ” (Gruber, 1995) (Car-

doso and Sheth, 2005).

The usefulness of the ontology can be clearly seen

from its various characteristics. However one aspect

which has great importance is that the conceptualiza-

tion must be shared. Thus when designing the on-

tology concepts that are being described and the re-

lations established between them, the ontology con-

cepts must be agreed upon and understood by multi-

ple stake holders, or the ontology itself will have little

to no use (Guarino et al., 2009).

Much of the ontology life cycle is like that of the

software engineering life cycle. It follows the path of

assessment, implementation, review, reﬁnement (Sure

et al., 2009). During the review and reﬁnement stages,

the ontologies are often accessed both for the knowl-

edge they are representing and the relations they ex-

press, much like metrics applied to software during

the veriﬁcation and validation stages. The parallels

between ontologies and software is extremely appar-

ent in this engineering model.

2.2 Designed for Reuse

As described in one of the seminal papers on ontoo-

gies (Gruber, 1995), often when designing ontologies

they are designed with reuse in mind. Much of the

engineering life cycle presented in (Sure et al., 2009),

focusses on the ability to use the ontologies for mul-

tiple purposes and the notion of generalization when

applying an ontology to various domains. Consider-

ing the time and complexity put into developing these

structures, it is wise to reuse them as much as pos-

sible. “Furthermore, in cases where an ontology is

reused, (e.g. as the basis for building a new ontol-

ogy rather than starting from scratch) descriptions of

how the ontologies are applied are terse or absent”

(Uschold et al., 1998). This represents an obvious gap

in the technology.

There has also been work done developing frame-

works for reuse such as that seen in (Gillespie et al.,

2011). Here the authors developed a framework to

design ontologies that can be reused across different

types of ontology driven compositional systems.

2.3 Who is the User?

It is important to understand that an ontology user

may not be an ontology expert. It is not necessary

for a user of software to be an expert programer, and

the same holds true for an ontology. Ontologies are a

complex structure to design and implement; once es-

tablished any user should be able to query them for

information. It should not take an expert to under-

stand the intricate nature of an ontology to use one.

Many software developers understand how to call a

system function but may not necessarily understand

how the call functions; the same is true for ontolo-

gies, as a user should be able to query an ontology

without knowing every class which exists in one.

Some users are interested in extending existing

ontologies to meet their needs, and will require more

in-depth understanding of how the ontology is con-

structed. This could be provided through extensive

documentation for an ontology. A user may also want

to know the intellectual rights of an/group of ontolo-

gies to assess weither or not they can freely share

them within their project. This information is as im-

portant as the ontologies themselves.

3 ONTOLOGY DISTRIBUTION

As described in the sections previous, it is difﬁcult to

design, engineer, and validate an ontology. Ideally a

user should be able to search for and reuse existing

ontologies. However currently it is not clear how to

locate ontologies and even if an appropriate ontology

was found, how should the user reuse it (Maedche

et al., 2003). “A breakthrough in ontology technol-

ogy would require methodological aids and tools that

enable effective and efﬁcient development. A key as-

pect in achieving this is successful re-use of ontolo-

gies” (Ding and Fensel, 2001). This can be achieved

through either a library or a repository.

“An Ontology library system is a library system

that offers various functions for managing, adapting

and standardizing groups of ontologies. It should ful-

ﬁll the needs for re-use of ontologies. In this sense,

an ontology library system should be easily acces-

sible and offer efﬁcient support for re-using exist-

ing relevant ontologies and standardizing them based

on upper-level ontologies and ontology representation

languages” (Ding and Fensel, 2001). Though this def-

inition encapsulates a majority of what is required in

ontology library systems there is other information

needed to satisfy all requirements as described above.

Additional aspects which should also be consid-

ered when developing such a system, are the notions

of trust, quality, and information on who published

the ontology. When using ontologies for important

life critical tasks such health and medicine it is im-

portant to understand that the creator of the ontology

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was qualiﬁed to capture said knowledge. For instance,

you would not want a history professional designing

an ontology on the intricate interactions between can-

cer cells; it would be much more preferable that the

ontology was published by an organization or indi-

vidual who is actively researching cancer.

Versioning information should include informa-

tion such as what the nature of the change was from

the previous version to understand if the change was

an addition, a subtraction, or worse yet a modiﬁca-

tion of existing relations. This is incredibly important

when considering whether or not to update the current

ontology being used to a newer version. If the ontol-

ogy is critical to the system’s functionality it may be

wise to hesitate before adopting the newest version of

the ontology.

The last and most important aspect to consider

when designing any type of ontology distribution sys-

tem is the user. As described above, the user should

be made central in any of these system implementa-

tion, as the key goal for any library is for mass adop-

tion and by targeting the user we will be able to have

wider adoption of these types of systems.

3.1 Current Methods of Distribution

In this section we will examine existing ontology

repositories. We will take note of the features they

offer and critique them against the needs described in

the section above.

3.1.1 BioPortal

BioPortal is a project that aims to store and distribute

biomedical ontologies (Noy et al., 2009). These on-

tologies are produced by the biomedical community

and uploaded to this application through a web portal.

One of the key goals of BioPortal is to create an open

access repository where users can upload new ontolo-

gies, edit and annotate current ontologies as well as

provide mappings between existing ontologies within

the repository. Additionally, users can push changes

and notes to current users of the ontology.

BioPortal implements a search feature where,

“Users can search for terms within an ontology or

across all BioPortal ontologies. Searches can be re-

stricted to class names, properties or other attributes.

Searches can also be based on exact matches or

soundex. In addition, users can search ontology meta-

data to ﬁnd particular types of ontologies. BioPortal

contains a master index of all ontology content and

metadata to streamline these searches” (Rubin et al.,

2007).

Since BioPortal heavily relies on the community

for maintenance, support, mapping, and upkeep of the

ontologoies, the only notion of quality is via a crowd

sourced rating system. Users who have used an on-

tology found on BioPortal can upload the project it

was used on and write comments/review (Noy et al.,

2009). This puts an incredible onus on the projects

which use an ontology to take time out of their devel-

opment cycle and leave comments about the ontology.

As with many of the ontologies found on BioPortal,

currently most do not have any ratings or reviews as-

sociated with them.

3.1.2 SOR

SOR (Scalable Ontology Repository) is a system de-

signed to store, search, and reason against many on-

tologies (Lu et al., 2007). It uses a relational database

to store the ontologies and queries are applied to them

using the SPARQL language. This project was used to

develop a system prototype to manage semantic mas-

ter data (Lu et al., 2007).

Though a majority of this project was focused on

how to reason against multiple ontologies, they did

however implement a faceted search to ﬁnd and view

existing ontologies. The information these inquires

would return are things such as a URI, textual descrip-

tion, list of classes, list of subject relations, and a list

of object relations (Lu et al., 2007).

This method is an interesting example of an on-

tology repository because it uses database schemata

to describe the metadata of an ontology. Furthermore

it allows for the potential of using this data for deep

reasoning on the ontologies stored within the system.

3.1.3 Lightweight Ontology Repository

The Lightweight Ontology Repository enables the

sharing of ontologies between multi-agent systems

(Pan et al., 2003), it was design so that ontology

designers and agents can use this system with com-

mon web standards to publish and retrieve ontologies,

along with associated metadata. The agents could ac-

cess ontologies via a REST-style web service. With

this project we see more emphasis put onto extra data

associated with the ontology. Much like SOR, this

repository keeps track of additional data via each on-

tology’s metadata.

The metadata stored within this system is the same

as the source Description Frame Work Schema. This

ontology keeps track of information such as the on-

tology name, language, version and brief description,

as well as information about the creator and how to

contact them (Pan et al., 2003). This additional data

gives a more complete understanding of the ontology

being stored within the system, however it does not

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give a complete view. It is an abstracted view and fur-

ther processing needs to be done to understand what

the ontology is actually describing. The agents would

need to have a pre-existing knowledge of which ontol-

ogy they needed and could validate against the meta-

data to conﬁrm that they received the correct ontol-

ogy.

Though this system was designed with a speciﬁc

domain in mind, it did emphasize the need to store and

keep track of each ontology’s metadata. However this

system lacked search functionality due to the fact that

the only way to receive ontologies was through re-

quest of exact ontology names. There is no notion of

trust or quality within this system; the users or agent

must assume that all ontologies stored within the sys-

tem are valid and the information they are describing

is accurate.

3.2 Proposed Method

As seen in previous sections many of these meth-

ods treat ontologies as ﬁles which are to be searched

through. This is much like searching through source

code for functionality. Unlike traditional markup lan-

guages like XML which only have ﬂat data descrip-

tions, ontologies have live and vibrant relations that

may change once reasoned upon. In software engi-

neering one of the key principles is that all elements

of a package are modular and serve a speciﬁc task and

thus these modules could be easily re-appropriated

for different tasks. Since ontologies serve a function

much like software this would lead to the conclusion

that they too should be a self-contained entities, which

are closed and consistent but still have facilities for

extension (Maedche et al., 2003). This leads to the

analogy of the software library.

This method would see ontologies grouped within

packages, describing knowledge within a similar do-

main. Additionally these packages could be stan-

dardized and documentation could be developed to

aid with distribution and understanding to the user

we described in 2.3. Furthermore these packages or

“Libraries” of ontologies could be standardized and

controlled by experts of a speciﬁc domain to ensure

quality, and consistency throughout all of the ontolo-

gies being distributed. This places a fundamental shift

in responsibility of creation, production, and quality

control to the creator of the ontology and removes

substantial burden from the end user.

In this system, ontologies within any package

would have to conform to a standard meta-ontology

(described in detail in 3.2.1). This ontology would al-

low for detailed information about the syntactic and

semantic entities stored within the ontology along

with pertinent information about versioning, creation,

controlling body, change information, intellectual

property rights, as well as potentially add facilities to

help stream line merging and mapping of external on-

tologies.

Finally, many software libraries have a review

committee which gives rational to the inclusion or ex-

clusion of functionality. This already has parallels in

the ontology world; some of the most well known and

most used ontologies are often controlled by a speciﬁc

body and changes are released through them with ra-

tionales. For example, the Dublin Core and Friend of

a Friend (FOAF).

3.2.1 The Meta-ontology

Much like the proposed use of a meta-ontology in

(Pan et al., 2003), (Maedche et al., 2003) offers an

alternative meta-ontology. (Maedche et al., 2003)’s

ontology meta-ontology (OMO), describes key terms

of the ontology, which project it has been used in,

who the creator was and what are their credentials,

the location of the ontology, etc.. This ontology is

displayed in Figure 1.

Figure 1: Ontology Meta-Ontology(OMO) (Maedche et al.,

2003).

Though this ontology is relatively detailed it still

lacks some key features necessary for use within our

proposed library system. A notion of domain needs

to be applied to this ontology, as to assert ontologies

within the speciﬁc instance of the library belong to

that domain. A notion of change and version is nec-

essary as well (this is described in detail in section

3.2.2). For additional robustness and extendability it

is necessary to add facilities to handle merging and

mapping.

There are also social factors we can add to the

meta-ontology to give a more complete description

of the ontologies being stored. One such element is

intellectual property and use rights of an ontology.

This would be incredibly important in a business set-

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ting where you would not want clients to redistribute

ontologies that contained important company data.

Links to documentation could also could aid the user

in further understanding of the rationale and relation-

ship meaning of the ontology. The last aspect that

could be added is the language in which the elements

of the ontology are described, be it English, Spanish,

Polish, Chinese, etc., and offer different translations

of the ontology if they exist.

3.2.2 Version Information

Version information is very important when dealing

with ontologies over time. Dependencies change, re-

lations change, and ultimately the structure of the on-

tology will change. In the method being proposed

change will be categorized as follows:

1. Additions - when entities or relations are added to

the ontology

2. Subtractions - when entities or relations are re-

moved from the ontology

3. Modiﬁcations - when entities or relations are

changed within the ontology

Figure 2: A visual representation of the types of changes

which can be applied to an ontology.

Additions have the least impact on the overall

structure of the ontology, since new information is be-

ing added to give a more complete description within

the ontology and should have little to no effect on

the existing relations. Subtraction can have a larger

impact on the ontology as it is removing informa-

tion from the ontology; this could affect the end user

as they may have relied on this information in their

application. Modiﬁcations have the most impact on

the ontology and the largest ramiﬁcations to the user.

Since the structure and relations change the reason-

ing and conclusions the ontology originally provided

will change. This will affect an end user’s application

dramatically.

“It has been argued that ontology versioning,

and, in particular, compatibility determination, can-

not be performed automatically” (Heﬂin and Pan,

2004)(Flouris et al., 2007), and thus the necessity of

integrating detailed notion of versioning within this

library system to aid users on deciding whether or not

to use the most current version of an ontology.

3.2.3 The Review Process

Many of the systems reviewed in this paper strictly

use user-based rating systems to review or rate the ef-

fectiveness of an ontology. (Noy et al., 2009) heavily

relays on the assumption that a satisﬁed user will post

reviews on used ontologies, along with the informa-

tion where the ontology was applied.

With a library model, a review will occur before

a new version is released. This ensures that only on-

tologies of the upmost quality are released. Preferably

the creators/maintainers of the library will review its

contents, ensuring that it conforms to the library stan-

dards, as well as any modiﬁcations will not change

focus or integrity of the ontologies being distributed.

This kind of release model can be seen through

the C/C++ and Java standard libraries as well as the

Linux kernel project.

3.2.4 Library over Repository

The method should be independent of domain as on-

tologies are ontologies, much like source code will be

source code. One could make domain speciﬁc appli-

cations but essentially each application will be no dif-

ferent than the applications that proceeded it. Much

like software libraries, functionality may be vastly

different but distribution within packages is standard-

ized. This makes deployment simple, which in turn

makes descriptions managable, and ultimately sim-

pliﬁes the distribution process. The standardization

makes the ontology make sense in any ﬁeld.

Therefore, the idea of doing text search through

complex structures is of limited value. Ontologies

are complex functional objects, with properties and

relations that need to be understood to comprehend

what the ontology describes. Keyword searches of-

ten results in objects with the most of the entities the

same but it may not have any relationship to what

the ontology itself describes. While the repository

relies heavily on keyword based search, the library

being proposed uses a meta-ontology to link all on-

tologies within the library. This allows for reasoning

based searches, which provide more accurate results

than simple keyword based searches (Maedche et al.,

2003).

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The beneﬁts of ontology libraries are standardiza-

tion across all domains and a facility for deep mean-

ing searches.

4 DISCUSSION & CONCLUSIONS

The ontology library proposed within this pape, is not

just a technical implementation but more of new ap-

proach to this problem. Often when teams set out to

create an ontology library/repository they have a set

of features they wish to implement although they may

not be considering the needs of the user. After imple-

mentation there is little literature examining its suc-

cess. When designing a system with a library in mind

there are several existing metrics we can apply to the

library to see if it meets the criteria necessary to pro-

mote usability. With the aid of software metrics we

can validate that the library system itself is ﬂexible,

reusable, extendable, and has met almost any needs

of a possible user (Frakes and Terry, 1996).

Fundamentally the system being proposed is shift-

ing the onus of evaluating, validating, and understand-

ing the ontology to the system and creator. This is log-

ical as the creators should have the best understand-

ing of what the ontology is supposed to be represent-

ing. With this shift, comes standardization through

the meta-ontology, giving much more context to what

is contained in an ontology opposed to just its title and

entity relations.

The meta-ontology proposed takes into consider-

ation social aspects which are not necessarily consid-

ered, that of intellectual property and documentation.

Systems like those seen in (Noy et al., 2009) and (Lu

et al., 2007), offer statistics on the number of classes

and relations and do not go into deeper description of

their meanings.

Finally the review panel: the organization who

produces an ontology library needs to take responsi-

bility and control of all changes, and future iterations

of the library for this method to work.

Though there exists many systems which try to of-

fer a ﬂavour of ontology repository, they often lack

the depth and breadth need to have a true non-domain

speciﬁc method to share, distribute, and discover on-

tologies.

ACKNOWLEDGEMENTS

The authors would like to thank the Guelph Ontology

Team for help and support while developing these re-

search ideas.

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