東海大学紀要情報通信学部
Proc. Schl. ITE Tokai Univ.
vol.5,No1,2012,pp.13-19
Vol.5 No.1,2012,pp. -

Paper
Paper

Knowledge Memory System Design on Virtual Space
by
Boonprasert SURAKRATANASAKUL *1 and Kazuhiko HAMAMOTO *2(received on April 6, 2012 & accepted on July 3, 2012)

Abstract
On knowledge management strategies, knowledge engineer needs to explore a lot of past knowledge
according to a current situation and then pile the new ideas upon. The difficultly is to find an appropriate way
for managing and maintenance huge information on a schematic way.
Knowledge memory system on virtual space is a scenic representation of huge information that is organizedspatially and temporally. It enables knowledge engineer to visually grasp and explore the information space foraccommodate new information at an appropriate place based on manner understandable in knowledge
management concept. We apply two schemas for knowledge space with CommonKADS concept, are called“Knowledge Landscape” and “Knowledge Atlas”. Knowledge landscape schema focus on capture andinvestigate on related group of knowledge structure. Knowledge atlas schema focus on understand of an
introduction to enterprise knowledge. Both of two schemas are correlated with “Knowledge Card” that consistsof meta-knowledge and hyperlink information within XML file.
Keywords: knowledge memory system, knowledge modeling, knowledge management, knowledge landscape,knowledge atlas .

1. Introduction

This system is a scenic representation of huge information thatis organized spatially and temporally on a virtual space. It
forenables users to visually grasp the global nature of knowledge,

managing knowledge of an organization that embedded in

explore the information space, and accommodate newpeople, processes and information generators. It views

information

knowledge as a valuable asset for value-added organization.

understandable [3, 4].

Knowledge Management is an important way

Many organizations define their own knowledge managementatanappropriate

place

based

on

users

To develop the system, we create two schemas forstrategies for explicating, developing and distributing theirmodeling the knowledge virtual space. They are applied fromknowledge in order to stay competitive and be innovative [1].

the CommonKADS methodology concept in two levels:

One of the purposes of knowledge management is that

Knowledge level and Organization knowledge level. For

people could share their explicit and/or tacit knowledge with

Knowledge level, we develop a schema name “Knowledge

others in an organization. In order to achieve this goal,

Landscape”. On the other hand, we develop schema nameknowledge engineer needs to discover the past knowledge“Knowledge Atlas” for Organization knowledge level. Each

information according to a present situation and then pile newof level has an individual perspective space for managing andideas upon them, as known as synergy knowledge mechanism

maintains knowledge within their concept, and both are[2]. Unfortunately, it is not easy manageable if they lack of acorrelated with the “Knowledge Card” that represent

good overview for give a big picture in an understandableknowledge item in domain.

manner.

To address issues, the rest of the paper is organized as

From above reason, this paper purposes an approach forfollows: section 2 briefly reviews about the relevant concepts:

design the knowledge memory system on the virtual space.

the CommonKADS background concept with the Knowledge
level in subsection 2.1 and the Organization knowledge level*1 Graduate School of Science and Tech., Tokai Univ.
*2 Dept. Infor. & Media Tech., School of Infor. andTelecommunication Eng., Tokai Univ.
Vol.5 No.1, 2012

in subsection 2.2. Subsection 2.3 describes an architectural―1―− 13 −

Knowledge Memory System Design on Virtual SpaceTimes, Times and Timesmodel view and UML extension mechanism that areknowledge is similar to the higher levels of functional

background mechanism for develop the knowledge schema.

decomposition in software engineering, but also includes

Section 3 describes two knowledge schemas and theircontrol over the functions involved [9]. Task can be

definitions: the Knowledge Landscape in subsection 3.1 anddecomposed into subtasks or into basic inferences. At thethe Knowledge Atlas in subsection 3.2. For section 4, welowest level of task decomposition, the tasks are linked to thedescribe framework of the knowledge memory system on

inferences and transfer functions.

virtualspace,

theknowledge

representation,

and

the

topological of knowledge. Section 5 describes the knowledge

2.2 CommonKADS’s Organization Knowledge Level

scenario development life cycle and an example. Finally,

CommonKADS

section 6 is the conclusions and future works.

methodology

is

one

of

prominent

technique for managing organization knowledge. It provides
an extensive method for describing business processes in

2. Relevant Concepts

which knowledge-intensive tasks are carried out. It deploys as
the technological means for capturing and managing both

2.1 CommonKADS’s Knowledge Level
CommonKADS methodology originates from the need to

explicitbuild the industry-quality knowledge systems on a large scale,were no longer limited to the emulation of expert reasoning;in a structured, controllable, and repeatable way [5]. It helps

they could also be applied to managing the enterprise

to clarify the structure of a knowledge-intensive task andknowledge such as, business rules, procedures, and guidelines.

human power bases, resources, process breakdowns, andOrganization

knowledge assets [10].

knowledge level.
In CommonKADS’s knowledge level, it consists of three

2.3

knowledge category that each capturing a related group of
structure:

Domainknowledge,knowledgeon such areas as: structure, process, people, culture andbut in this research, we use only two levels for develop theknowledgeofconducted based on problems and opportunities. It can focus

CommonKADS methodology concept consists of three levels
and

part

develop and understand an organizational aspect. The study isof UML to develop the knowledge schema model. Generally,

level

as

the series of worksheets to support knowledge engineer forsoftware engineering [6]. Meanwhile we can use the standard

Knowledgeknowledge

In organization knowledge level, CommonKADS provides

has an essence structure that similar to analysis models in

system:tacit

management initiative. The capabilities of CommonKADS

provides a specification of data and knowledge structures. It

purposedandArchitectural

Model

Mechanism
In CommonKADS

Inference

knowledge, and Task knowledge.

View

procedure,and

UML Extension

knowledge

engineer

explains the knowledge structure by the modeling. Domain- Domain knowledge specifies the domain specificknowledge model is designed with the notation similar toknowledge and information types. Its modeling implies

UML class. Task and Inference knowledge have own

capturing the static structure of information and knowledge

graphical notations, as nondirective UML equivalent [11].

types. Just like in regular data modeling, a schema is

These appear an ambiguous to understand on different theconstructed containing the major types and relations occurring

notation meaning. On the other hand, in organizationin the application domain. Ordinarily, domain knowledge

knowledge level provides the suite of worksheets fordescription consists of two types: Domain schema anddeveloping an organization aspect. Nevertheless, they lack ofKnowledge base [7].

a good understanding in a comprehensive picture of how anorganization uses its knowledge [12].

- Inference knowledge describes the basic inference steps
that want to make using domain knowledge. It describes how

For solving above problems, we apply the concept ofthese static structures can be used to carry out a reasoningarchitectural model view and UML extension mechanism forprocess. In software engineering term, Inferences represent

all artifacts to be one standard for creating the knowledge

the lowest level of functional decomposition [8]. The main

schemas.

ingredients of the inference knowledge are: Inference,- Architectural model view deals with abstraction, with

Knowledge role, and Transfer function.

decomposition and composition, with style and esthetics. It- Task Knowledge describes what goals and application

use a model composed of multiple views to describe thepursues, and how these goals can be realized througharchitecture [13]. In research, we use only two views that

decomposition into subtasks and ultimately inferences. Task

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Proc. Sch. ITE
Tokai University

Boonprasert SURAKRATANASAKUL and Kazuhiko HAMAMOTO

Times Times Times Times Times

related to the knowledge paradigm for creating the knowledge

Domain Knowledge

schemas: Logical view and Functional view.
Logical view is a primarily supports what the system

structured

Concept

should provide in terms of services. In this view, the system isdecomposed into a set of key abstractions, taken mostly frominstanced ofKnowledge Base

the domain in the form of objects or object classes. For thefunctional view, it supports how the system’s elements work

Rule Type

together seamlessly by usage scenario. We use this view toRelation

described

Knowledge Instancedescribe the corresponding script like the inference structure
and task knowledge scenario.

Logical view
Functional view

- UML extension mechanism is provided by the UML
standard in order to allow users to customize and extend thelanguage to suite their particular needs. It consists of three
types: Stereotype, Tagged value, and Constraint [14].
Stereotype is an extension of the vocabulary which allows<<stereotype-name>>or

specialext. info.

functioncomposed

Task Knowledge

properties which allows designer to create new information inthat element specification. General form of tagged value is:

StaticDynamic(user-defined)

stereotype icons. Tagged value is an extension of theKnowledge roletransferred

Transfer

specific to the domain problem. General form of stereotype isact asI/O role

Inferencedesigner to create new building blocks from existing ones buteitherused

Inference Knowledge

Task

realized

Task Method{tag=value}. Lastly, Constraint is an extension of thesemantics. It represents rules that are applied to model.

Fig.1 The Knowledge Landscape Schema.

Designer can employ both predefined and user-definedconstraints. Constraints may also be defined using the Object

Table 1 Element Description of Knowledge Landscape Schema.

Constraint Language (OCL) [15].

Element

3. Knowledge Schemas
Knowledge

schemaisapatternthat

Domaincreatesforexplanation the concept of knowledge model on virtual space.
and Knowledge Atlas schema.

3.1 Knowledge Landscape Schema

Packagecontainsthedomainspecific

Knowledgeknowledge and information types.

Knowledge

Package contains the instances of types

Base

It has two schemas in research: Knowledge Landscape schema

Description

specified in domain schema.

Inference

Package

Knowledge

invocation of inference method.

Task

contains

thespecificationofPackage contains the suite of reasoning

Knowledge landscape schema focus on capture andKnowledge

function.

investigate on the knowledge category. It helps to clarify theConcept

Metaclass represents the category of things

structure of a knowledge-intensive task and provide awith abstract concept.

specification of data and the knowledge structure. Knowledge

Relationlandscape schema consists of two perspective views: logicalofview and functional view. Logical view provides abstract forview

realizesthescenarios

from

the

Rule typeknowledge-intensive task that correspond with the inference

anddefinedthrougha

Metaclass

used

for

categorizationandspecification of knowledge.

and task knowledge by Inside-Out and Outside-In realization[16]. Fig.1 shows the knowledge landscape schema forknowledge level. The description of schema elements are
itemized in Table 1.

Vol.5 No.1, 2012

modeling

specification of arguments.

representation of domain knowledge and knowledge base.
Functional

Metaclass used for more complicated types―3―− 15 −

Knowledge

Metaclass of instances of domain knowledge

Instance

concept.

Knowledge Memory System Design on Virtual SpaceTimes, Times and Times

Element
Inference

Description

position in

Structure

Metaclass describes the lowest level offunctional decomposition on carrying out

Peopleholdderivedapply

primitive reasoning steps.
Knowledgerole
Dynamic
knowledge role

Metaclass defines the functional roles ofKnowledge

required

Type of knowledge role in run-time inputs

Resources

Type of knowledge role that specifies thecollection of domain knowledge that is

Functions transfer information between

function

reasoning agent and external entities.

governedachieved
Functionused to make the inference.
Transfer

used
Processand outputs of inferences.

Static

Goal

Rule

Fig.2 The Knowledge Atlas Schema.

Metacalss defines the reasoning function

Table 2 Element Decription of Knowledge Atlas Schema.

and invokes the corresponding task method.

Element
Task Method

appliedknowledge in reasoning process.

knowledge roleTask

derivedPower

Formalize method control structure.

Structure

Description
Metaclass represents an organization isbuilt from structural units.

3.2 Knowledge Atlas Schema
Knowledge atlas is a schema that captures the essential

Function

Each structural unit carries out one or morebusiness functions.

features of real system. It starts with an understanding of thebroader an organizational aspect. It argues that models are

Process

important for understanding working mechanisms within

Process describes how the work is done
within business.

context and environment of knowledge-based system, such as:

Peopleorganization aspect, agents, and tasks. In addition, it

People play roles in the organization andfill positions in Structure.

contributes the understanding of the sources of knowledge,
inputs and outputs, flow of knowledge and identification ofPowerother variables such as the impact that management action has

People derive power from their role andknowledge.

on the knowledge of organization.

Resources

Although different organization’s systems have different

The objects are used or produced in thebusiness.

goals and internal structures, they use similar concepts to

Knowledge

describe their structure and operations [17]. Fig.2 shows theKnowledge

items

characterizetheknowledge in the organization at a fairy

schema of knowledge atlas for organization knowledge level.

general level of description, mainly for

The description of schema elements are itemized in Table 2.

managerial purposes.
Goal

4. Knowledge Memory System on Virtual Space

The purpose of the business or the outcome
is trying to achieve.

Rule

Knowledge memory system on virtual space has an

A statement defines or constraints some
aspect of the business.

objective view enables user to edit contents on surface byusing geographical and topological correlation [18]. For thissystem, knowledge (contents) is visually placed based onThisknowledge schemas and the prospective of virtual spaces.

mechanism

knows

as

the

Synergyknowledgemechanism that results from the spiral of knowledge

Thence, all of them are continuously synthesized by the fusion

development and SECI (Socialization – Externalization –of knowledge and filtrate by rearrange within the knowledge

Combination - Internalization) model [19].

topology.

―4―− 16 −

Proc. Sch. ITE
Tokai University

Boonprasert SURAKRATANASAKUL and Kazuhiko HAMAMOTO

Times Times Times Times Times

4.1 Knowledge Representation(t = 0)Configure

For added the acquired knowledge to the system,thevirtualknowledge memory space.

knowledge must be transformed into the knowledge item that
represents with XML-formatting file, are called “Knowledge
Card”. Knowledge card is composed of meta-knowledge and(t = 1)iithe hyperlink of information body. Meta-knowledge is the

Push

i

i

abstract of information body and hyperlink of information

knowledge

instances.

ibody obtains the detailed content of knowledge. We can acesstheto the information body through the hyperlink, so as toimplement the integration of operations.

(t = 2)ii

In knowledge card structure, it consists of three tag parts:i

card name, description and hyperlink of information body.

Synthesizeiandknowledgeifiltrate
instance

relationship.

Fig.3 shows a sample of knowledge card in an XML file.
Considered tag of XML file, the <card> element represents a
unit of a knowledge item. It contains three child elements:<name>, <description>, and <bodylink>. The <name>Find correlated concept

i

C

C

i

element contains a name of knowledge card that impile to(t = 3)iiand develop group ofiknowledge base.

knowledge item, the <description> elements contains theshort abstraction of knowledge item, and the <bodylink>element contains the URL of an embedded file (e.g., an image,ia movie clip, a slide, and so on).

iC<?xml version=“1.0” encoding=”UTF-8”?>Ci(t = n)

i

i

i

C
i

i

i

<card version=“1.0”><name>

Checked BIOS </name>r<description>rr

inference

Check BIOS setting that compatibility with memoryrr

inference</description><bodylink> IT_SUPPORT/BIOS/chkBIOS.mpg </bodylink>

Fig.4 The Topological of Knowledge and</card>Filtration Developing.

Fig.3 A Sample of Knowledge Card (Knowledge Instance).

5. Knowledge Scenario Development Life cycle
4.2 Topological of Knowledge

Knowledge scenario is the sequencing that related to theOn the virtual knowledge memory space, it comprised ofstep of inference knowledge usage. It similar likes theknowledge card that has own latitude, longitude, andzooming

value

for

determineuser’sviewpoint.

functional decomposition and method in the computer

The

programming. Typically, each of knowledge scenarios has angeographical value of card enables user to judge the location

only one individual goal to achieve.

reply on knowledge schemas and spatial clues. Fig.4 show

To develop the knowledge scenario, user might determine

the topological of knowledge card and filtration developing.

the chronicle order to the inference knowledge elements, such

Notation in Figure 4:iKnowledge Instance from Domain knowledge.

C

Concept from Domain knowledge.

rKnowledge Role from Inference knowledge.

inferenceas, Inferenec and/or Transfer function. The chosen inference
knowledge display its ordering number and the linking line tothe others on a step,as a task knowledge. The structure andlength of scenario depend on the situation occurs and theInference from Inference knowledge.

irsolution to achieve a goal. User can edit the knowledge

Role of Knowledge instance inscenario by rearranging or combining old and new theInference step.

inference knowledge as a life cycle. Fig.5 shows theknowledge scenario developing: Scenario (A) and Scenario(B) and their reusability.

Vol.5 No.1, 2012―5―
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Knowledge Memory System Design on Virtual SpaceTimes, Times and Times

A5

B1
inference

inference. Some of inferences from Task (a) and (b) could

inference

B3

shared, for example, Inference (a2) and (b1). Because ofinferencethese inferences contain the knowledge instances that have

A4, B2same concept, for example, VirtualUniverse and WTuniverse

inference X
A1
inference

are the knowledge instance that have the concept of creating

B4
inferenceof virtual area.

A3, B5

A2
Transfer Fn.

inference Y

6. Conclusions
Managing knowledge through knowledge memory system

Fig.5 The Knowledge Scenario (A) and (B) andis an important part of knowledge management initiative. The

Reusability of Inference X and Y.

understanding of knowledge content and organization context
From Fig.5, Knowledge scenaio (A) represents withis a critical success factor for the knowledge-based systemthick-line has the 5 steps (A1-A5). Knowledge scenaio (B)development. We use the CommonKADS methodology

represents with dot-line has the 5 steps (B1-B5). Both ofconcept to be the guideline for develop the schemas ofknowledge scenarios have two shared-inferences: Inference X

knowledge content and organization context: Knowledge

and Y.

Landscape and Knowledge Atlas. We use two schemas for
identify, formalized and arranging knowledge on the virtual
space. On the virtual space, we represent knowledge item by

5.1 Example

Knowledge Card. Each of knowledge cards composed ofThis example describes two task knowledges that have anlatitude, longitude and zooming values that determine the user

aim to write a basic 3D program. Task (a) is written by

field of vision. To delivery knowledge, user creates theJava TM 3D [20] and Task (b) is written by WorldToolKitTM

knowledge scenario in the series of knowledge cards. The[21].

advantage for define knowledge in a scenario are reusability
and modifiability. User can create a new knowledge scenario

Task (a): Java 3DTM

with previous knowledge and filtrate knowledge forward to

a1. Create a Canvas3D object.

the sustainable knowledge memory system.

a2. Create a VirtualUniverse object.
a3. Create a Locale object, attaching it to the VirtualUniverse

Reference

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a4. Construct a view branch graph.
a4.1 Create a View object, ViewPlatform, PhysicalBody,
and PhysicalEnvironment object.
a4.2 Attach Canvas3D, ViewPlatform, PhysicalBody, andPhysicalEnvironment object to View object.
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b1. Create a WTuniverse.
b2. Entered simulation by calling WTuniverse_go.
b3. Read sensors.
b4. Call Universe action function.
b5. Perform object tasks.
b6. Play/Record paths.
b7. Render the Universe.
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Proc. Sch. ITE
Tokai University

Boonprasert SURAKRATANASAKUL and Kazuhiko HAMAMOTO

Times Times Times Times Times

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