iBusiness, 2010, 2, 370-376
doi:10.4236/ib.2010.24048 Published Online December 2010 (http://www.scirp.org/journal/ib)
Copyright © 2010 SciRes. iB
An Innovative Approach about the Process
Knowledge Representation in the Processes of
Large Cluster Projects Management
Yong Liu, Qiong Chen
School of Business Administration, South China University of Technology, Guangzhou, China.
E-mail: liuyong@scut.edu.cn, cqjoanchen@163.com
Received July 28th, 2010; revised September 7th, 2010; accepted October 23rd, 2010.
The features of the large Cluster projects’ management processes, complexity, “one-off” and “irreversibility”, make
the projects’ process knowledge hard to be expressed, analyzed and obtained accurately. It is also not convenient to be
accumulated and disseminated, and can’t be learned and used by managers. However, such knowledge is the crystalli-
zation of human wisdom. It has an important role in promoting efficiency of projects management and increasing ac-
cumulation of social knowledge. A better way is needed to find for its representation and utilization. From the perspec-
tive of cluster project management department, this article takes a cluster project’s construction as an example, and
proposes a suitable method for the process knowledge representation in large cluster projects’ management processes,
combined with the Topic Maps and MFFC-
& MLD-
Keywords: Cluster Projects, Process Knowledge, Knowledge Representation
1. Introduction
With rapid development of economic and social progress,
large-scale trend of projects becomes more and more ob-
vious. A number of complexity cluster projects covering
many areas in large scale, distributed information and
Cross Specialized fields are emerging, such as Olympic
project, Expo project, and Asian Games projects. Mainly
composed of a number of large projects, these luster pro-
jects are generally carried out under cluster project man-
agement department. They need huge investment and
have huge influence in the world [1]. Meanwhile, large
cluster projects with large scale and complexity processes
usually aim at particular purposes. With “one-off” and
“irreversibility” feature, they are calling for “one-off
things done” [2]. It is a high demand for projects man-
agement, and also a challenge to cluster project manage-
ment department’s management and policy-making.
Processes of large cluster projects’ management by
government have rigorous characteristics and contain a
lot of knowledge, which is hard to be accumulated, or-
ganized and represented because of the characteristics of
the large cluster projects, such as complexity, one-time
and irreversibility, but has a great guide and good refer-
ence for other similar projects’ management, and has
great significance in the improvement of the project re-
sults, the project efficiency, even the accumulation of the
whole society’s knowledge. If the process knowledge in
large cluster projects’ management can’t obtain better
representation, acquisition, sharing and dissemination, it
will be very difficult to guide the projects’ implementa-
tion. Problems in the projects can’t be solved intermedi-
ately; time of the projects’ construction can’t be man-
aged efficiently; project funding can’t be used sensibly
and the whole projects can’t be completed in accordance
with the intended targets. How terrible the results are!
We need to create a convenient and practical process
knowledge representation method to express process
knowledge which are comprehensively, clearly and com-
pactly contained in cluster projects’ management, if we
want to access, share and transfer it. That is the problem
which needs to be studied and solved urgently.
2. Process Knowledge and Process
Knowledge Representation
Process knowledge includes procedures, relevant regula-
Supported by “the Fundamental Research Funds for the Central Univer-
sities, SCUT”, project number: 2009ZM0115.
An Innovative Approach about the Process Knowledge Representation in the
Processes of Large Cluster Projects Management
Copyright © 2010 SciRes. iB
tions and knacks to achieve specific targets of the task.
It’s a kind of procedural, methodological and combina-
tional knowledge mostly obtained from the practice of
“doing”. The actives and the relationships between are
the cores of it [3].
Currently, major representation methods of process
knowledge are graphic representation, ontology repre-
sentation and so on. Graphic representation, such as
process knowledge map [4], MFFC (multi-factor flow
chart), MLD (multi-level text), hierarchical task network
[5], data flow diagram [6], super-graph model [7], and
the event process chain [8], is an illustrated knowledge
representation method which is easy, clear and concise.
Ontology representation is the dominant representation
of concept model. On surface, there are not many differ-
ences between “ontology” and data dictionary. They are
both collection of many terms. But ontology is more rig-
orous and precise than data dictionary in content. The
grammar and the axioms of ontology should be elabo-
rated in precise and formal language, syntax and clear
defined semantics, such as the PKOR [9] program based
on KIF, IDEF5 [10] and system modeling [11], the XML
language description [12] and so on. However, these
approaches were often used in enterprises for the repre-
sentation of business process knowledge but can’t meet
with the requirements of the large cluster projects be-
cause of their characteristics of large scale, high techni-
cal difficulty, long construction period, and complexity
environment [13].
3. Characteristics of Process Knowledge in
the Processes of Large Cluster Projects
The processes of large cluster projects management are
complex and changeable. So process knowledge con-
tained in it is very complicated and diverse. To represent
process knowledge well, we should have a more in-depth
knowledge and understanding of its characteristics.
In the processes of large cluster projects management,
the order of management processes is very clear for indi-
vidual project. Only after the accomplishment of the first
step, can the second step be put into practice. So, strong
sequential representation methods of process knowledge
should be better for its representation. However, if stand-
ing in the management level of large cluster projects, we
can find that, there are no very strict order relations
among the components. To achieve the objective as soon
as possible, with sufficient funding, personnel, materials
and so on, many projects are parallel implementation,
and are not appropriate to use strong sequential process
knowledge representation methods. Evidently, a single
process knowledge representation method can’t be a
good way to represent the process knowledge in the
processes of large cluster projects management. A more
appropriate approach is to combine a strong sequential
method with a non-strong one, integrate their advantages
and form a new representation method.
Topic map is a knowledge representation model simi-
lar to semantic network. Combining the advantage of
traditional indexing, library science, artificial intelligence
and any other fields, it can organize the knowledge effi-
ciently to probe, infer and solve questions caused by
large number of disordered information [14]. It’s a suit-
able method for the representation of non-strong sequen-
tial process knowledge in the processes of large luster
projects management.
MFFC- & MLD- (the improved multi-factor flow
chart and the improved multi-level text), which were
proposed by Dr. Guo Weisen, is a representation method
based on MFFC & MLD. MFFC- expresses main
process steps in process knowledge, while MLD- ex-
presses activities and relations in detail. Descriptions of
knowledge input and output are added to MFFC-, so
that the document knowledge can correspond to the
management processes, and be managed well. MFFC
-& MLD- is a suitable method to express strong
sequential process knowledge in the processes of large
cluster projects management [15].
Therefore, this article try to combine topic maps with
MFFC-& MLD-, and to create a new and suitable
method for better representation of process knowledge in
the processes of large cluster projects management. That
will lay the foundation for process knowledge’s sharing
and transferring.
4. Topic Map and MFFC- & MLD-
4.1. Topic Map [16]
The topic map can be used to describe and manage the
complex information word. It consists of three basic
elements: Topic (T), Occurrence (O) and Association (A).
Topic can represent any meaningful projects, such as
name, organization, concept, location, etc. It is a basic
unit in topic map to express knowledge. Any object
which can lead the user to discuss should be included in
it. Based on application requirements, topics can be di-
vided into different categories, named topic types. A
topic type is also a topic. The relationship between a
topic and a topic type is equivalent to that between a
class and its instance. A topic can link to one or more
related information resources. Description of these re-
sources is called the occurrence of the topic, and usually
exists in the form of documents, Web pages and so on.
Association means the relationship between two or more
An Innovative Approach about the Process Knowledge Representation in the
Processes of Large Cluster Projects Management
Copyright © 2010 SciRes. iB
topics. Like topics, association can also be divided into
different categories, called association types. For exam-
ple, “among the…”, “participate in …” and so on. Asso-
ciation types are also topics, and are defined in the form
of topics. Among topics, all types of relationship which
are organized and linked by associations will form a
knowledge network. Just through T, O, A these three
elements, topic maps organize information resources,
establish indexes, and construct semantic network by
describing the relationships among topics. So they sup-
port the accurate location of interested knowledge points
and related information resources.
4.2. MFFC-& MLD- [15]
MFFC-& MLD- are proposed on the base of MFFC
& MLD. The basic syntax elements of MFFC contain the
based map of body– time, activities rectangular box, re-
lationship arrows (different arrow types mean different
relationships, including four relationships: order, and, or,
and xor) and time line. Based on MFFC, MFFC- adds
knowledge input and output, and closely combines flow
technology with knowledge which is needed or obtained
or produced in the processes of projects management, as
is shown in Figure 1 and Figure 2.
MLD- is the detail description of activities and rela-
tionships in the MFFC-. It adds descriptions of know-
ledge input and output based on MLD, as is shown in
Figure 3 and Figure 4.
5. The Study of Representation Method
According to the characteristics of large cluster projects’
management processes, combined with topic map and
MFFC- & MLD-, the new representation method of
process knowledge in the processes of large cluster pro-
jects management is that
Figure 1. The schematic diagram of MFFC.
Figure 2. The schematic diagram of MFFC-.
The figure number of the corresponding MFFC:
Activity ID:
Activity Name:
Main Body:
Relationship number:
Relationship description:
Figure 3. The schematic diagram of MLD.
Step one: Take each component project as a topic and
divide the large cluster projects
Large cluster projects are composed of a number of
large construction projects which have no strict order
relations but sharing, occupation, mobility relations
among funds, staff, and materials. It is suited for the rep-
resentation method of topic map and can be classified
into various topics. If the number of components is large,
we can firstly classify topic types, and then topics.
Step two: Sort out and number the documents pro-
duced in the management processes
There are many files and documents in cluster project
management department’s management processes. They
are important parts of knowledge input and output.
Numbered by different topics, operational links or types,
they will be more conducive to be found and used. This
An Innovative Approach about the Process Knowledge Representation in the
Processes of Large Cluster Projects Management
Copyright © 2010 SciRes. iB
The figure number of the corresponding MFFC-:
Activity ID:
Activity Name:
Input (the needed knowledge):
Output (the generated knowledge):
Relationship number:
Relationship description:
ab ilit
Figure 4. The schematic diagram of MLD-.
step is the base of MFFC-& MLD-’s drawing. Do-
cument numbering can be carried out during the projects
implementation processes. Timely classification will
help the acquisition of processes knowledge.
Step three: draw MFFC- charts under each topic
As the whole implementation processes of one single
large project have strict operational processes, its man-
agement process knowledge can be represented clearly
and coherently by MFFC- charts.
Step four: draw MLD- charts for activities and rela-
tions in the MFFC- charts
Drawing MLD- charts is to obtain detail descrip-
tions of activities and relations in MFFC- charts. It can
describe the projects’ process knowledge well. In the
meantime, a MLD- chart is also a bridge between top-
ics and occasions. It links topics and projects’ manage-
ment knowledge (the management files) and forms an
organic whole to represent the projects’ process knowl-
edge completely.
Step five: systematic integration
All the steps above are not isolated, but integrated to-
gether systematically. They are interrelated and comple-
mentary. Systematic integration can make the form of
representation clearer, content more complete, and proc-
ess more convenient.
Systematic integration can be divided into four levels:
the top level is the topic layer of cluster projects. The
second level is the layer of MFFC- chart correspond-
ing to each topic. The third level is the MLD- chart
layer. The fourth level is the occasion layer which is the
set of the documents in the processes of management.
Each level is closely linked, as is shown in Figure 5.
6. Case Study
This representation method of process knowledge in
large cluster project management has already applied in
some management processes of cluster project’s con-
struction. For example, a project is composed of seven
major parts including athlete village, technical official
village, mass media village, sports venues, press center,
administrative service area and Theme park. It is pre-
sided and planned by the cluster project management
department and regarded as a typical large cluster project.
Because, there are many projects involved, we can clas-
sify the topic types by the projects’ types at first. Then,
classify topics, as shown in Figure 6.
Taking the building of gymnastics stadium as an ex-
ample, we can draw a MFFC- chart of the manage-
ment processes after numbering the documents generated
in the management processes systematically. The MFFC-
chart in creation stage of gymnastics stadium con-
struction is as shown in Figure 7.
Among them, taking the activity of feasibility analysis
as an example, the corresponding MLD- chart is as
shown in Figure 8.
Finally, we combine project topics, MFFC- charts,
MLD- charts, and documents (events) generated in the
management processes together, and they form a system
integration map of the Cluster projects as shown in Figure
9. Thereby, it can clearly express the process knowledge
in the processes of Cluster projects management.
7. Conclusions
Because of different characteristics of large cluster projects,
there are many difficult issues in representation, acqui-
sition, analysis and sharing of large cluster project’s
Figure 5. The integration schematic diagram of process
knowledge’s representation method in the large cluster pro-
ject management.
An Innovative Approach about the Process Knowledge Representation in the
Processes of Large Cluster Projects Management
Copyright © 2010 SciRes. iB
Cluster project management
officials village
service area
History museum
Beach volleyball
Mass media
Figure 6. The topics’ partition chart of cluster project management.
Figure 7. MFFC- chart in the creation stage of gymnastics stadium construction.
An Innovative Approach about the Process Knowledge Representation in the
Processes of Large Cluster Projects Management
Copyright © 2010 SciRes. iB
MLD-——the activity of feasibility Analysis (01-01-03)
The corresponding figure No. of MFFC-: 01-01
Description: the MFFC- chart in the stage of project creation of
gymnastics stadium’s construction
Activity number: 01-01-03
Activity name: Feasibility analysis
Basic attributes
Body: Li××, Wang××, Zhao××
Action: To making the feasibility analysis of gymnastics
stadium’s construction
roject application stage
Extended attributes
Prerequisite: Gymnastics stadium’s construction had passed
the initial assessment
Constraints: None
Participate: Li××, Wang××, Zhao××
Input(knowledge needed): GD-40-01 demand information
Output (knowledge generated): GD-30-01 feasibility analysis report
Figure 8. The corresponding MLD- chart of feasibility analysis activity.
Cluster project management
Mass media village
Sports venues
Technical officials village
Athletes village
Press center
Beach volleyball
Project creation
Project planning
Project financing
Project implementing
MFFC- layer
Project proposal
Initial assessment
Feasibility analysis
Project application
Project assessment
MLD- layer
Demand information
Management norm in
project creation stage
Project proposals
Feasibi lit
Administrative service area
Theme park
Figure 9. The system integration map of the cluster projects’ process knowledge representation.
An Innovative Approach about the Process Knowledge Representation in the
Processes of Large Cluster Projects Management
Copyright © 2010 SciRes. iB
management process knowledge. However, there is a
large number of process knowledge in the processes of
large cluster projects management which can be learn-
ed and be re-used. It is necessary to express, analyze,
access, Share and transfer process knowledge in the
management processes. Combined with the Topic
Maps and MFFC- & MLD-, this article forms a
new method of process knowledge representation and
gives specific implementation steps. It lays the founda-
tion for analysis, acquisition, sharing and transferring
of the knowledge, and provides relevant reference for
the management of similar projects. This method is
simple, clear, easy to understand, and has wide appli-
cation prospect.
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