The Globalization of Manufacturing in the Digital Communications Era of thest
21 Century: Innovation, Agility and the Virtual Enterprise
Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98# 77
Collaborative Development and Use of
Ontologies for Design
H. Takeda, M. Takaai, and T. Nishida
Graduate School of Information Science
Nara Institute of Science and Technology
8916-5, Takayama, Ikoma, Nara 630-0101, Japan
Phone: +81-7437-2-5261
Fax : +81-7437-2-5269
Email: takeda@is.aist-nara.ac.jp

Abstract
In this paper, we introduce ontology-centric knowledge organization approach torealize design knowledge base system for sharing and reuse of knowledge. Since
ontology is used here as an intermediate level of information representation
between the model and media level of information, it can work to bridge multiple
models and multiple users. DesignersAmplifier is a workbench for designers where
they can store, organize their information resources, and also can communicate toother designers based on the ontology-centric knowledge organization.
DesignersAmplifier helps designers to organize documents with ontology. For
example, it can re-build documents as hypertexts of which hyper-links are linked toconcepts in ontology. It can help designers to expand search words by ontology orby collocation data in documents. DesignersAmplifier can help communication
among designers by exchanging ontologies. We realized exchanging ontologies bymobile agent architecture.
Keywords
ontology, cooperative design, mobile agent, information organizing

IFIP PROLAMAT 98 - September 9-10-11 & 12, 1998 Trento, Italy

The Globalization of Manufacturing in the Digital Communications Era of thest
21 Century: Innovation, Agility and the Virtual Enterprise
Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98

1

INTRODUCTION

Rapid growth and spread of information technology especially network technology
enables people to use computers more naturally and easily and as a result, theirworking style is changing, i.e., style of designers' work is also changing. It isespecially significant on information gathering. Once main information sources fordesigners were their experience that was stored as drawing and documents written
on paper, or human communication among colleagues, manufacturers, andcustomers. Now they can access not only their past documents and drawings bycomputers but also various kind of related information on the network. They cancommunicate with other people more rapidly and frequently by computer.
Capability of information gathering is significantly increased. It is good news fordesigners to have good facilities for information access, because design is getting
so complicated that more various information should be taken into account.
But such information flood can make designers confused, because they do notknow how to use such enormous information effectively for their designing work.
It does not denote incapability of designers but incapability of the current
information technology. The current information technology like information
gathering (for example, Knoblock and Levy (1995)) and information extracting(Cowie and Lehnert, 1996) mainly concerns how to obtain condensed informationfrom broad information sources objectively. It is suitable for search problems for
public information sources like newspapers. But design is more intensive andconstructive work. We need a new technology to handle intensive and structurized
information.
In the following sections, we will show our attempt for the above purpose, whichis called DesignersAmplifier. DesignersAmplifier is a workbench for designers
where they can store, organize their information resources and also cancommunicate to other designers.

2

DESIGN AS KNOWLEDGE ORGANIZATION

Design is a process of creating new artifacts, more precisely creation of
specifications of new artifacts for manufacture from given requirements (Takeda etal., 1990). Although it is a visible and apparent process in design, there is another,usually invisible but also important process in design, namely, re-organization ofknowledge. When a new requirement is given to designers, they sometimes survey
their internal knowledge like experience and expertise, and sometimes collectexternal knowledge like books and catalogs in order to solve the given
requirement. Such introduction of new knowledge and re-interpretation of existingknowledge cause designers' knowledge to re-organize in order to adapt current andfuture design tasks.
For example, suppose that a designer is given a required specification of productof which one of performance is greater than those he has designed. He would
examine his past cases to check whether they could satisfy the requirement, find
how to improve the performance somehow, and design a new product bymodifying one of past cases. This example does not seem creative in ordinary
sense, but even it contains re-organization of knowledge. He learned how the

IFIP PROLAMAT 98 - September 9-10-11 & 12, 1998 Trento, Italy

The Globalization of Manufacturing in the Digital Communications Era of thest
21 Century: Innovation, Agility and the Virtual Enterprise
Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98

performance is achieved and reached a new conceptual configuration or structure
for the product that could lead a new product satisfying the requirement.
Design is not always done by a single designer, rather team or group design iscommon activity. In such case, since knowledge is sharing among designers, reorganization of knowledge should also be shared, i.e., re-organization ofknowledge is done in communication among designers. For example, suppose thata designer could form a new concept. It should be transferred to other designers,
examined and sometimes modified by them, then finally shared.
In this paper, we do not seek theory or formalization for re-organization ofknowledge itself, rather seek how to support such activity. The key issue is how to
support designers' conceptualization process and exchange of concepts among
them.

3

ONTOLOGY-CENTRIC KNOWLEDGE ORGANIZATIONIn this section, we discuss how designers organize heterogeneous information andshow an architecture for such knowledge organization.

3.1 Information Levels
Most crucial part of information organization is not in well-structured information
but in unstructured one. Designers use various kind of information from physicalmodels to natural languages. We have usually paid attention to so-called ``models'',e.g., 2/3D model and some mathematical model like thermodynamics andkinematics. Since models are well investigated and understood, there are many
books and studies to handle them. But models are not sources but results ofknowledge organizing formed after much engineering and scientific effort.
Individual designers have tried to capture unstructured information, and some
excellent and common organization of information could become models.
In design process, required specifications are normally given as human oriented
or human understanding media such as natural languages. On the other hand,product specifications as results of design are in many cases given as machineoriented media or machine understanding or mathematically formalized media likegeometric models, because current manufacturing methods are governed bycomputers. Focusing on representation media, design is a process that translates
descriptions by human-oriented media to those by machine-oriented media (seeFigure 1). Although it is a big gap, designers can somehow find the way to bridge
them using their knowledge on objects and models and experience on design.
The same situation happens on communication among designers. Designers
sometimes exchange information through human-oriented media and sometimes
through machine-oriented media. We need systematical way to bridge both media.
In this paper, we propose an intermediate media level between human-oriented andmachine-oriented media. Function of this level is to provide fundamental relations
between what both types of media. In our approach, it is a level in which only
syntax is provided, and called "formalization level". Syntax is used to explicate
structures in human-oriented media and it can also have some relations to
structures in machine-oriented media. Structure in the formalization level is thus
understandable both for human and machines.

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The Globalization of Manufacturing in the Digital Communications Era of thest
21 Century: Innovation, Agility and the Virtual Enterprise
Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98

EngineerEngineer

Human-oriented media

Computer-oriented media

Product

Figure 1 Levels of Information

3.2 Roles of Ontology in Cooperative Knowledge Organization
We adopt the formalization level as ``ontology'' in this paper. Although ontology
cannot capture all functions of the formalization level, it can offer indispensableconnection between the media and model levels.
Ontology is a term in philosophy and defined as ``the branch of metaphysicalenquiry concerned with the study of existence itself'' (Flew1979). In AI
community, an ontology is defined as ``an explicit specification ofconceptualization''(Gruber 1993) that is intended to use as base for knowledge
representation. Ontology is represented as systems of symbols in computers, i.e.,
symbols and their relations that represent concepts and their relations. Ontology
commits only declarative nature of systems of concepts because its purpose is toprovide consent for knowledge representation, e.g., identification of concepts.
Therefore ontology is adequate as representation for the formalization level.
We here propose a new approach for knowledge based systems called ontologycentric knowledge organization. In this approach, roles of ontology are two-holds.
One is as method of organizing knowledge that is further categorized as follows;
1. Ontology is used to structurize information from various sources by using its
structure.
2. Ontology is used to bridge between the human-oriented and the computeroriented level representation.
3. Ontology is used to bridge between multiple designers.
The other is as a kind of knowledge which itself should be acquired and organized.
Ontology also should be accumulated, refined, and organized in the system. In
order to include incoherent and simultaneous information activities, ontology
should be multiple. Then it is important how to deal with relations among multiple
ontologies. We have proposed formalization of multiple ontologies by modal logic
in Takeda et al. (1995) and shown practical methods of integrating multiple
ontologies in Takaai et al. (1997). In this paper, we focus on the former aspect of
ontology.

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The Globalization of Manufacturing in the Digital Communications Era of thest
21 Century: Innovation, Agility and the Virtual Enterprise
Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98

Personal Information Space

Ontology
Designer: Information Organizing Agent
Documents

Mail

Drawings: Information Exchanging Agent

Figure 2 Architecture of DesignersAmplifier

4

CONCEPT OF DESIGNERSAMPLIFIER

DesignersAmplifier is our current prototype system to support designers
continuously from the human-oriented level to the computer-oriented level, which
is based on ontology-centric knowledge organization approach. The basic idea of
this system is to provide a information space for each designer where agents assist
designers' access to information sources, organization of acquired information, andcommunication to other designers (see Figure 2). Designers can access information
sources with support of DesignersAmplifier, e.g., by adding related information, atthe same time DesignersAmplifier can collect designers' behavior by monitoring
their information access. Information access and communication is sometimes
purely in media level, sometimes in both media and formalization levels, andsometimes in media, formalization, and model levels. DesignersAmplifier mainly
supports media and formalization levels, and can connect model-centered systems.
Each designer can do his information activities through DesignersAmplifier so that
DesignersAmplifier can maintain his personal information space.
DesignersAmplifier also assist him to compose his ontology by providing various
information organizing facilities like statistical analysis and ontology-based
information classification. Thus he can evolve ontology more which can in turnstrengthen information organizing facilities of DesignersAmplifier. This cycle canrealize autonomous development of knowledge organization.

5

D/AMP 1.0: IMPLEMENTATION OF DESIGNERSAMPLIFIER

We have implemented prototype of DesignersAmplifier called D/AMP 1.0 that isbased on agent architecture. There are personal information spaces provided forindividual designers, and agents to process specific tasks on them. There are
documents, ontologies, and agents on personal information spaces. Agents can read
information on spaces and produce and put new information on them. They canalso move other personal information spaces to find and retrieve information.
Designers can order some tasks to agents or manipulate documents and ontologies
by referring results from agent execution (see Figure 2).

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The Globalization of Manufacturing in the Digital Communications Era of thest
21 Century: Innovation, Agility and the Virtual Enterprise
Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98

D/AMP is implemented as server (personal information space) and client(interface), and server is realized by Scheme and Java on workstation, and client is
by Java on WWW browser.

5.1 Representation of ontology
We adopt frame ontology (Gruber 1993) as basis of representation of ontology, i.e.,
ontology is is-a hierarchy of concepts. A class represents a concept. Each class has
its name, expressions, and slots. An expression is description how the concept is
appeared in media like documents. A slot represents an attribute of the concept,
and is described as a slot name, a class for attribute value, and an attribute value.
Super-sub relation represents a relation that implies inheritance. Connective
relation represents other relation

5.2 Information Organizing
Our policy for ontology construction is not automatic ontology generation but
computer-aided ontology building, i.e., the system supports designers to build
ontology by showing related information. Basically only designers can develop
concepts on ontology but they can use various analyzed or organized information
which information organizing agents can present designers by using ontology on
the environment.
Document-structurizing agent modifies documents so that words in documents
can refer corresponding concepts in ontology. Collocation-computing agent
computes collocation of words in document sets. Word-weight-computing agent
computes the word weight by keyword vector method (Salton and McGill, 1983).
Document-search agent searches documents with the collocation data and the word
weight. Word-similarity-computing agent computes the word similarity fromcollocation data and other information. Information such as search result,collocation data, word weight and word similarity, is presented and used bydesigners to make design documents and ontologies.

5.3 Exchanges of ontologies among designers
In DesignersAmplifier, designers can collect concepts in other designers'
ontologies. It is realized by mobile agent architecture. A mobile agent sent on a
mission can visit other personal spaces, extract related concepts on them, and bringthem back to the original personal space.
A serious problem with distributed information resources is how to find mutual
relations among them. There are two ways to achieve interaction among distributed
information resources. One is to provide special agents or facilities that can advice
appropriate resources for given problems. Such facility is realized as information
broker (Fikes et al., 1996) or mediator (Wiederhold 1992)(Takeda et al., 1995).
The advantage is that no new mechanism is needed for information resources. The
disadvantage is that broker or mediator should know contents of information
resources in advance. On the other hand, mobile agent architecture can adapt

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The Globalization of Manufacturing in the Digital Communications Era of thest
21 Century: Innovation, Agility and the Virtual Enterprise
Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98

Figure 3 Collected concpets by mobile agents
dynamically changing information resources although it requires new mechanism
embedded in information resources. Since personal information spaces fordesigners change their contents dynamically, we adopt the latter approach.
We introduced a mobile agent mechanism in DesignersAmplifier and provided
ontology-collecting agent.

5.3.1

A mobile agent mechanism

Agents and their information environments or places are basic components ofmobile agent architecture (White 1996)(Rothrmel and Popescu-Zeletin 1997). An
agent works with information on information environment where it resides or with
communication with other agents. There can be multiple environments so thoseagents can move from one environment to another.
In D/AMP, an environment corresponds to a personal information space, andagent to either an information organizing module or an information-exchanging
module between personal information spaces. As implementation, a mobile agent
is defined as function in Scheme, and Scheme processes exchanges function codes
through TCP/IP.
Since it is not secure that mobile agents can do as same as other static agents inpersonal information agents, we provide manger agents that control access frommobile agents to personal information space, i.e., every access is done throughmanager agents. We also provide router agents that assist mobile agents todetermine which space they should go. A mobile agent can prepare which space itwould go around in advance or determine it depending on spaces that it would
visit. In the latter cases, router agent can suggest spaces related to the current
space. There are manger and router agents in each personal information space.

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The Globalization of Manufacturing in the Digital Communications Era of thest
21 Century: Innovation, Agility and the Virtual Enterprise
Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98

Figure 4 Outlook of DesignersAmplifier (1.0)

5.3.2

Ontology-collecting agent

Using the mobile agent mechanism, we provide ontology-collecting agent thatsearch and bring back systems of concepts in ontologies on other personal
information spaces.
Ontology-collecting agent first receives a keyword list from a designer. It obtains
a space to visit next by asking router agent on the current space, and then moves tothe specified space. It then searches related concepts in the ontology on the
personal information space, and stores a copy of the concepts and their relations.
Then the ontology-collecting agent again tries to move next space that the router
agent on the space that knows relevant spaces to the current space. Finally, theontology-collecting agent goes back to the initial personal information space, andput the all stored concepts and their relations. Figure 3 shows that the ontologycollecting agent put concepts and their relations related to keyword "bike".
"House" icon stands for concept in ontology and "Figure" icon for agent. The agent
visited two other personal information spaces, and captured "bike" concepts andsome related concepts to it. Since it found "bike" concepts in both two spaces,
there are two concepts named "bike". Although names are the same, we canunderstand that hey have different sub and super concepts by referring otherconcepts collected together.

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The Globalization of Manufacturing in the Digital Communications Era of thest
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Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98

6

EXAMPLES OF USE OF DESIGNERSAMPLIFIER (D/AMP 1.0)

Here we show how DesignersAmplifier (D/AMP 1.0) works by using the protocol
data in a bicycle rack design (Cross et al., 1996). The protocol is a text data of
conversations so that it is poorly organized.
The aim of this experimental use is to examine (1) organizing of protocol data,(2) design knowledge extraction from protocol data, and (3) re-usability of protocol
data with search mechanism.

6.1 The protocol data in a bicycle rack design
The theme of the protocol is the design of rack to fix backpack to mountain bikeeasily. Three designers, who did not know the bicycle design so much, discussed
the theme with some materials and data. The protocol data (about 1500 lines) is
made by conversations of discussion. In this experiment, we divided the protocol
into small text segments by twenty lines to compose a document set. And we
picked out 240 concepts from the protocol and built ontology with them and thesuper-sub class relations.

6.2 Editing ontology
Figure 4 is a screen shot of the browser of DesignersAmplifier (D/AMP 1.0). The
right part of window is ontology window in which designers can browse and edit
ontology on his personal information space. Icons stand for class concepts, andblue arrows for super-sub class relations and green arrows (not appear here) for
other relations. Right bottom pop-up window shows the concept edit window.
Designers can look at definitions of concepts and edit them in this window. Here,the window shows the concept of clip. It has an expression 'clip' and a slot 'cost'that belongs to money class.

6.3 Browsing and search design documents
Figure 4 also shows the search result. When designer checks reference concept"clip" in right ontology browsing window, the system puts the search result in left
window. Left top window shows a document list ordered by evaluation value of
search result. Left bottom frame shows the content of a document that is selectedfrom the above the document list by designer. This document is structurized one,i.e., some words are hyper-linked with concepts on ontology. Designer can retrievea part of ontology related to the document by clicking these hyper-links. For
example, the word "clip" is linked to the concept "clip" on ontology. Collocationbased search method is chosen in this example.

6.4 Collocation computing
Table 1 is a part of collocation data calculated with the protocol. Each pair of aword and a number indicates a word and its collocation value. The table shows top
10 words for "clip". Most of these words actually have some relations with clip in
the protocol. For example, the words "wire" and "strap" are fixing devices as sameas clip.

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The Globalization of Manufacturing in the Digital Communications Era of thest
21 Century: Innovation, Agility and the Virtual Enterprise
Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98

word
frame
bag
pack
thing
bike

Table1 Collocation of word "clip"
value
word
value
10.9
wire
2.6
10.0
outside
2.4
5.6
strap
2.4
5.0
back
2.4
5.0
slip
2.3

6.5 Re-usability experiment
We performed a simple experiment to evaluate our system. The purpose of theexperiment is how users can re-use protocol data by using our information
organizing methods. We prepared the scenario that a user searches and investigates
the parts of protocol in which designers discussed fixing methods of backpack on
bicycle. We prepared subjects who have not seen this protocol. We compared
performance with our system and with the Unix command "less". Time limit is anhour for each subject. Each subject is requested to search six or seven locations inwhich designers discussed fixing methods either by our system or "less" command.
The correct answer we prepared is three locations.
With "less" command, the only one location that user answered is a correct
answer, but with our system, the user detected all three correct answers. Mainly,
the user found them with the following ways.
1. The user obtained the collocation words of some fixing method words(e.g., "strap").
2. The user obtained the related words on ontology.
3. The user searched the documents with these reference words and read the top
three or four documents.
The experiments show that information-organizing facilities that we provide areuseful to understand documents rapidly. Understanding documents in design is notachieved by simply searching documents, because specifications for searchthemselves are not well defined. When we want to search information for design, it
often happen there are only vague or incomplete specifications for search, forexample, only some of keywords are remembered and others not. In order to makespecifications more complete and concrete, we should sometimes expand them andsometimes squeeze them. Information organizing facilities can help suchprocesses. For example, referring to ontology helps users to expand their
specification for search based on background knowledge, consulting collocation
data is to help users based on features of the given document set, and reading somestructurized documents assists users to refine specifications by understanding
individual relations among concepts.

7

DISCUSSION AND CONCLUSION

Most relevant approach is work by Dong and Agogino (1997). We agree with themthat unstructured information is crucial for design and that we should pursue todevelop to process such information.
But difference is the basic assumptions for unstructured information, andtherefore methods to deal with it are different. As we mentioned Section 3, we

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The Globalization of Manufacturing in the Digital Communications Era of thest
21 Century: Innovation, Agility and the Virtual Enterprise
Proceedings of the Tenth International IFIP WG 5.2/5.3 Conference
PROLAMAT 98

assume three layers for design information. Our claim is that unstructured
information should have relations to more structured information like ontology.
We have provided methods based on ontology. As we have shown in networkbased information gathering, ontology-based search is reliable and effective inpruning unintended information (Iwazume et al., 1996).
But as Dong and Agogino mentioned, pre-defined ontology is not useful becauseof dynamics of design. The important feature of our approach is that unlike otherontology-based approaches (e.g., Gruber et al. (1992)) ontology itself should be
developed during design. Dynamics of design should be captured as ontology
development. Some of information organizing facilities can contribute ontology
development.
Another important feature of our approach is that our system is highlyinteractive. We did not introduce any techniques like machine learning, because
they are not mature enough to apply highly conceptual process like ontology
development. Instead, we provide various presentations for users andcommunication methods to others for ontology integration. Ontology integration isanother problem to solve. We have proposed some methods (Takaai et al., 1997),
but more work should be done for this problem.
Although the current implementation is not sufficient and not well tested, we
believe that we arose a new aspect for integration of design information andshowed a solution for it.

ACKNOWLEDGEMENT
This research was partially funded by IMS GNOSIS project, and the "Modeling ofSynthesis" project of the Japan Society of for the Promotion of Science's Research
for the Future Program under the contract number JSPS-RFTF 96P00701.

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BIOGRAPHY
Hideaki Takeda is associate professor in Artificial Intelligence Laboratory in
Graduate School of Information Science at Nara Institute of Science andTechnology (NAIST). He received his Ph.D. in Precision Machinery Engineeringfrom the University of Tokyo in 1991. He has conducted research on a theory ofintelligent CAD, in particular experimental study and logical formalization ofengineering design. He is also interested in multi-agent architectures andontologies for knowledge base systems.
Motoyuki Takaai is doctor candidate in Artificial Intelligence Laboratory in
Graduate School of Information Science at Nara Institute of Science andTechnology (NAIST). He received his B.E. from NAIST in 1995. His researchinterests include ontologies and multi-agent systems.
Toyoaki Nishida is professor in Artificial Intelligence Laboratory in Graduate
School of Information Science at Nara Institute of Science and Technology(NAIST). He received B.E., M.E., and Doctor of Engineering degrees from Kyoto
University in 1977, 1979, and 1984 respectively. His research interest covers
knowledge media, agent technology, knowledge sharing, and qualitative reasoning.

IFIP PROLAMAT 98 - September 9-10-11 & 12, 1998 Trento, Italy