MANAGING CHARACTERISTIC ORGANIZATION

KNOWLEDGE IN COLLABORATIVE NETWORKS

Ekaterina Ermilova and Hamideh Afsarmanesh

Collaborative Networks Group, University of Amsterdam, Kruislaan 419, 1098 VA Amsterdam, The Netherlands

Keywords: Ontology Engineering, Knowledge Modeling, Knowledge Management, Virtual organization Breeding

Environment, Organization’s Profile, Organization’s Competency.

Abstract: Modeling and management of the knowledge/information related to the organizations is fundamental to

efficient operation of the Collaborative Networked Organizations (CNOs). Continuous changes in different

aspects of involved organizations, is an unavoidable reflection to the dynamic changes in the demands of

stakeholders and customers in the market / society. Organizations’ profiles, and especially their competency

characteristics tailored to the requirements of opportunities emerging in the market, need to be modeled and

managed. Furthermore, mechanisms are required for handling the flexible representation and processing of

the organizations’ knowledge. Both research and practice have shown that the formation of collaborative

networked organizations requires pre-establishment of a cluster, also called a breeding environment. In this

paper we address the Virtual organizations Breeding Environments (VBEs), which provide the necessary

conditions and support for configuration and creation of Virtual Organizations (VOs). Using the ontology

engineering approaches, we present an approach for modeling of organizations’ knowledge inside VBEs,

and specify the ontology for their profiles and competencies. Furthermore, we present the required

mechanisms for management of the organizations’ knowledge, and specify the functionality required to

manipulate organizations’ information through the life cycle of VBEs. The paper also addresses the logical

design of a database for storage of organizations’ information and for the visualization of organizations’

profile and competency knowledge.

1 INTRODUCTION

Modeling and management of knowledge that is

gathered and generated by organizations is a

fundamental driver for organizations’ successful

operation in the market and society (Balakrishnan et

al, 1999) (Caie, 2007) (Afsarmanesh and

Camarinha-Matos, 2005). Existing networks/clusters

of are now eager to model and manage their

knowledge, accumulated across their environment,

in order to process and analyze it for discovery of

possibilities, and deciding on strategies for future

network evolution. In this paper we focus on

modeling and management of different

organizations’ knowledge within the Collaborative

Networked Organizations (CNOs). The CNO has

provided a new paradigm applied to many emerging

domains (e.g. domain of tourism, health care,

manufacturing, among others) in the market and

society. (Camarinha-Matos and Afsarmanesh, 2006-

a) gives the following definition for the CNO: CNO

is an alliance constituting a variety of entities (e.g.

organizations and people) that are largely

autonomous, geographically distributed, and

heterogeneous in terms of their: operating

environment, culture, social capital, and goals, that

cooperate/collaborate to better achieve common or

compatible goals, and whose interactions are

supported by the computer network. Unlike other

networks, collaboration in a CNO is an intentional

property that derives from the shared belief that

together the network members can achieve goals

that would not have been possible or would have

had a higher cost if attempted individually.

Supporting the main features of the CNOs, such

as scalability, dynamism and geographic

distribution, require the need for the ICT-based

management of CNOs. In our research we address

management of the CNO member organizations’

knowledge that constitutes the base for the entire

CNO management. We focus on a specific type

(Afsarmanesh and Camarinha-Matos, 2007) of

CNOs, namely the Virtual organization Breeding

Environment. We adopt the following definitions of

the Virtual organization Breeding Environment and

the Virtual Organization: Virtual organization

313

Ermilova E. and Afsarmanesh H. (2008).

MANAGING CHARACTERISTIC ORGANIZATION KNOWLEDGE IN COLLABORATIVE NETWORKS.

In Proceedings of the Tenth International Conference on Enterprise Information Systems - AIDSS, pages 313-320

DOI: 10.5220/0001709603130320

 SciTePress

Breeding Environment (VBE) (Afsarmanesh and

Camarinha-Matos, 2005) is a network of

organizations and some related supporting

institutions that adhere to a base long term

cooperation agreement, and adopt common

operating principles and infrastructures, with the

main goal of increasing their preparedness in

advance, towards potential collaboration within

Virtual Organizations. Virtual Organization (VO)

(Camarinha-Matos and Afsarmanesh, 2006)

represents a network of legally independent

organizations that come together and share

resources and skills to achieve common goals, such

as preparing a proposal or a bid, or jointly

performing the tasks needed to satisfy an

opportunity, while using the computer networks and

software systems as the base

communication/interaction infrastructure.

In VBEs, the member organizations’ knowledge is

mainly represented by their “profiles” (Afsarmanesh

and Camarinha-Matos, 2005) (Ermilova and

Afsarmanesh, 2007]. Considering the main aim of

collecting knowledge about member organizations’,

which is to enhance their involvement within VOs,

the main element of the profile is the organizations’

“competency” (Afsarmanesh and Camarinha-Matos,

2005). In this paper, we provide “extensive”

definitions for “organization’s profile” and

“organization’s competency” in VBEs:

Organization’s profile consists of the set of

determining characteristics (e.g. name, address,

capabilities, etc.) about each organization, collected

in order to: (a) distinguish and compare each

organization with others, (b) analyze the suitability

of each organization for involvement in some

specific line of activities / operations.

Organization’s competency is the main element

of the VBE profile that provides up-to-date

information about capabilities and capacities of

each organization, as well as conspicuous

information about their validity, qualifying it for

participation in some specific activities / operations

within the VBE, and mostly oriented towards the VO

creation.

This paper addresses our approach and

mechanism for modeling, specification and

management of VBE members’ profiles and

competencies. Our approach is based on the formal

specification of pre-defined ontologies for the

organizations’ knowledge in VBEs. The research

results, presented in this paper, further contribute to

the design and development of a Profile and

Competency Management System (called PCMS) for

VBEs, which is outside the scope of this paper, but

the topic for forthcoming papers.

Below in this Section, after discussion of the main

motivations for the ICT-based modeling and

management of member organizations’ profiles and

competencies, we address the requirements and the

identified research challenges. In Section 2, the

paper addresses the models for VBE member

organizations’ profiles and competencies, introduced

earlier in (Ermilova and Afsarmanesh, 2007).

Section 3 presents the ontologies developed to

support modeling and management of organizations’

knowledge in VBEs. In Section 4, the paper

specifies the ontology-based functionalities designed

for management of VBE member organizations’

profiles and competencies. Section 5 presents the

designs of both: the database and visual interface,

specified for the VBE member’s knowledge. Finally,

Section 6 concludes this paper.

As such, the main motivations for management

of detailed profiles and competencies of VBE

member organizations are listed by m-1 to m-8: for

profiles – (m-1) creation of awareness inside the

VBE, (m-2) selection of partners for new VOs, (m-

3) evaluation of members by the VBE

administration, (m-4) introduction / advertising in

the marker / society, and (m-5) identifying

competency gaps; specifically for competencies –

(m-6) matching VBE members’ competency details

against the risen opportunity, (m-7) determination

of VO’s competency, and (m-8) processing the VBE

members’ competencies.

Furthermore, the design and development of ICT-

based representation and management of the VBE

member organizations’ profiles and competencies

are motivated by the following: (i) In medium and

large VBEs (i.e. with more than 20 members) as

well as in geographically distributed VBEs, the only

way for all VBE members to get the up-to-date

information about each other is through computer-

based representation and distribution of their

profiles. (ii) Due to daily changes of customer

demands in the market and society, the profiles and

competencies of VBE members are dynamically

changing. In medium and large VBEs, the VBE

administration is not able to obtain and analyze up-

to-date knowledge about all members with such a

high level of dynamism. Thus, there is a need for

ICT-based submission and processing of the

members’ profiles and competencies facilitating the

VBE’s dynamism.

From our analysis of the VBEs, a number of

requirements are identified for modeling and

management of VBE member organizations’

knowledge are listed below by r-1 to r-5: for

modeling – (r-1) in order to be easily adopted by

VBEs operating in different domains (e.g. in

domains of tourism, health care, manufacturing,

etc.), development of unified/generic models is

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needed for organizations’ profiles and competencies;

for management - (r-2) support for continuous (e.g.

daily) updating of profile and competency data, (r-3)

handling the confidentiality of profile and

competency data, (r-4) support for adaptability of

the management approaches to the wide varieties of

VBE applications, and (r-5) support for

sustainability of the management approaches in

dynamic and expanding environments.

Among the technical challenges involved in

modeling and management of VBE member

organizations’ knowledge, the following challenges

of c-1 to c-7 are addresses by our approach: for

modeling - (c-1) support of different abstraction

levels from general knowledge classes to the

domain-dependent knowledge classes, and (c-2)

unification / generalization of different competency

representations / models as exists in research and

practice; for management - (c-3) common

understanding of profile and competency models by

all VBE members, (c-4) categorization in catalogues

of competencies, (c-5) unified naming of the

competencies and their standardization, (c-6) formal

representation of profile and competency data in

order to support their further semi-automatic

processing, and (c-7) semantic integration of the

different description of VBE members’ expertise

submitted to VBEs.

2 MODELING KNOWLEDGE OF

ORGANIZATIONS

The model, designed for organizations’ profile and

competency knowledge, represents the set of

knowledge classes, as well as the relationships

among these classes, that need to be collected and

managed in VBEs. These knowledge classes are

empirically identified through: (a) interviewing and

questioning the representatives of running VBEs,

(b) study of related work on organizations’ profiles

and competencies, and (c) study of existing

enterprise models and ontologies (Ermilova and

Afsarmanesh, 2007). A subset of classes and their

relationships representing the profile and

competency knowledge are addressed in Table 1 in

the form of a hierarchy, where elements labeled by 1

to 8 represent classes, and each “x.y” represents

either an attribute of the “x” element (e.g. “3.2”) or

another class that is related to “x”, e.g. “3.3”. Please

note, that Table 1 provides only the names of the

main knowledge classes identified for the VBE

member organizations’ knowledge model. The

detailed specification of this model is the subject for

a forthcoming paper.

A main objective for our research on knowledge

modeling and management is to distinguish among

the domain-independent knowledge classes (e.g.

common for all VBEs) and the domain-dependent

knowledge classes (e.g. related only to a specific

domain of activities, e.g. manufacturing). In this

paper we introduce the concepts of a “core-class”

and a “domain-class”. As such the knowledge

classes represented in Table 1 are the core-classes,

because they are generic enough to be presented in

all VBEs, independent of their domains / business

areas. Additionally, some of the core classes (e.g.

competency, resource, products/services, etc.) have

further domain-dependent sub-classes, i.e. domain-

classes. For example, within the manufacturing

domain the competencies can be classified by the

specific manufacturing activities, e.g. “metalworking

competency”, “welding competency”, “turning

competency”, etc. As such, the domain-classes can

be integrated into the generic profile / competency

model as the elements labeled by 3.1, 3.2, 3.3.1,

3.3.4.1, 3.3.5.1, 5.1, 6.1, 7.1, and 8.1 (i.e. italicized

elements in Table 2). The domain-classes shall be

arranged in the form of generalization hierarchies,

e.g. the “milling competency” and “welding

competency” are subclasses of “metalworking

competency” in the generalization hierarchy of

competencies for the metalworking domain. Such

hierarchies shall also support the categorization and

cataloguing of VBE member organizations by their

domain related characteristics.

Table 1: Hierarchy of the main knowledge classes in the

VBE member organizations’ knowledge model.

Label Elemen

1 General data 4

inancial data

2 Contact data

4.1

Annual balance

3Com

etencies

4.2

Annual revenue

3.1

Com

etenc

class

esources

3.2

Com

etenc

name

5.1

esource class

3.3

abilities

5.2

Resource name

3.3.1

abi

class

5.3

acities

(

ref. 3.4

)

3.3.2

abilit

name

5.4

Cons

icuities

(

ref. 7

)

3.3.3

Resources

(

ref. 5

)

roducts

3.3.4

Raw materials

6.1

Product class

3.3.4. Raw material class 6.2

Product name

3.3.4. Raw material name 6.3

Product markets

3.3.5

Standards

7 Cons

icuities

3.3.5. Standard class 7.1

Cons

icuit

class

3.3.5. Standard name 7.2

Cons

icuit

name

3.3.6

Products

(

ref. 6

)

7.3

Issue date

3.3.7

Cons

icuities

(

ref.

7.4

Issue

3.4

acities

7.5

iration date

3.4.1

Total rate

ssociated

artners

3.4.2

Available rate

8.1

ssociated

artner

3.4.3

Available time

8.2

Associated

artner

3.5

Cons

icuities

(

ref. 7

)

8.3

General data

(

ref. 1

)

8.4

Contact data

(

ref. 2

)

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315

3 SPECIFICATION OF

ONTOLOGY

We have introduced the concept of “VBE ontology”

in (Afsarmanesh and Ermilova, 2007). As such, the

VBE ontology represents a form of unified and

formal conceptual specification of the heterogeneous

knowledge in VBE environments to be easily

accessed by and communicated between human and

application systems, for analysis and evolution

purposes. The main objective of the VBE ontology

is the provision of support for knowledge modeling

and management in VBEs, particularly for: (1) the

establishment of a common semantic subspace for

VBEs, (2) the development of VBE knowledge

repositories, (3) the processing VBE knowledge by

software tools, (4) the enabling inter-organizational

learning & operation, and (5) the integratability of

VBE knowledge.

The structure of the VBE ontology consists of

four levels of abstraction and ten partitions

constituting sub-ontologies of the VBE ontology, as

also illustrated in Figure 1. The four levels of

abstraction, including the “meta” level, the “core”

level, the “domain” level, and the “application”

level, reflect the reusability of the VBE ontology at

different VBE domains and application

environments. For example all VBE applications

from the same domain share the ontology defined

for all the above levels and differ only at the

application level. However the ten ontology

partitions, such as the “VBE profile and competency

sub-ontology”, the “VBE history sub-ontology”, the

“VBE Bag of Assets sub-ontology”, etc., mainly

refer to the knowledge about the fundamental

entities and concepts in VBEs as being addressed by

different VMS sub-systems (Afsarmanesh et al,

2007). Please also note that in Figure 3, the

number/symbol represented inside the parenthesis

next to each ontology level represents the cardinality

of instances for this VBE ontology level, e.g. there is

only one VBE meta level ontology and one VBE

core level ontology common to all VBEs, while N

and M both represent “many”, e.g. addressing the

fact that there are many different domains / business

area ontologies for different VBEs and each VBE

domain / business area may in turn also have many

VBE application ontologies. Furthermore, the

decomposition of this ontology structure into levels

and partitions supports the incremental development

of the VBE ontology, and the developed parts of the

ontology can be reused by VBE management

subsystems for different VBEs.

VBE ontology aims at providing the

specifications for all VBE knowledge classes

through presenting the following properties for each

classes: (i) a definition of the concept, represented

by this class, (ii) a set of synonyms for the concept,

(iii) an abbreviation for the class’s name, (iv) a set of

subclasses of this class, and (v) a set of attributes /

relationships of this class.

Figure 1: Structure of the VBE ontology.

While the meta and core VBE ontology levels

are specified and constructed manually, the domain

and application VBE ontology levels must be

constructed on demand for each specific VBE

domain and application. The VBE core level

represents ten separate OWL (OWL, 2007) files that

were constructed using Hozo (Sunagawa et al, 2004)

and Protégé (Protégé, 2007) editors.

To support the modelling and management of

VBE member organizations’ knowledge, we use the

core and domain levels of the “VBE profile and

competency sub-ontology” as addressed below:

 VBE core profile and competency sub-ontology

(Figure 2) represents the core/generic profile and

competency model, as addressed in Table 1. The

main purposes and usage of the VBE profile and

competency core sub-ontology for the modelling and

management of organization’s knowledge in VBEs

includes the following: (1) Support of the R&D in

the VBE field through providing means for the

evolution of the organizations’ profile and

competency model by being an extensive, uniform

and sharable representation of these models. (2)

Support for the common understanding of the

structure of the profiles and competencies through

providing the extensive definitions of the related

concepts. (3) Support for semi-automated design and

development of a database for organizations’

knowledge (Guevara-Masis et al, 2004). (4) Support

for automatic structuring of the profile and

competency knowledge for its representation in a

GUI.

 VBE domain profile and competency sub-

ontology is a form of representation of the domain

classification for the organization’s profile and

competency model. The VBE domain profile /

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competency sub-ontology can be further partitioned

into several specific “sub-sub-ontologies” depending

on: a specific core concept (e.g. only for domain

resources), or a specific domain / business area (e.g.

only for welding). Figure 3 illustrates a sub-ontology

developed for the classification of

standards/practices and capabilities/processes in the

metalworking domain. The usage of the VBE profile

domain sub-ontology includes the following:

(1) Support of the representatives of the VBE

member organizations with the definition of their

domain-specific profile and competency related data

(e.g. identification of classes of the domain-specific

business processes performed within an

organization). (2) Support for representation of the

“standard names” and the “standard relationships”

for the domain-dependent profile and competency

knowledge that can be further facilitate the software-

based matching/processing of the knowledge. (3)

Support for automatic structuring of the domain-

dependent profile and competency knowledge in a

GUI.

Figure 2: Example partial screen-shot from the profile core

sub-ontology constructed in Hozo.

Figure 3: Example screen-shot from the ontology for

metalworking capabilities constructed in Protégé.

4 MANAGEMENT

FUNCTIONALITIES

Management of VBE member organizations’

profiles and competencies takes place through the

entire VBE life cycle (i.e. from the VBE creation

stage to the VBE dissolution stage). In this paper we

introduce eleven main functionalities identified for

the organizations’ profiles and competencies

management, as illustrated in Figure 4. All

functionalities are activated at different VBE life

cycle stages. In Figure 4, these activation times are

indicated next to each functionality’s name as

follows: [C] for the VBE creating, [O] for the VBE

operation, [E] for the VBE evolution, [M] for the

VBE metamorphosis, and [D] for the VBE

dissolution. Detailed description of the

functionalities, as well as of their support by the

VBE profile and competency sub-ontology, is

addressed below:

1. Uploading of Core Profile and Competency

Model. This functionality supports the uploading

and installation of the core profile and competency

model in the form of the VBE core profile and

competency sub-ontology and adaptation of the

database to this model (see Section 5 for more

details).

2. Customization of the Core Profile

Competency Model. This functionality supports

modification of the organizations’ profile and

competency models.

Figure 4: PCMS’s life cycle functionalities.

3. Uploading of Domain Classifications. This

functionality supports uploading and installation of

generalization hierarchies of specific domain classes

of profile and competency knowledge in the form of

VBE domain profile and competency sub-sub-

ontologies.

4. Customization of Domain Classifications. This

functionality supports updating of the generalization

MANAGING CHARACTERISTIC ORGANIZATION KNOWLEDGE IN COLLABORATIVE NETWORKS

317

hierarchies of domain classes, for example through

adding new domain-dependent profile knowledge

classes needed in a specific VBE application.

5. Registration of Organizations. This

functionality supports registration of VBE member

organizations in the system and thus creation of their

profiles.

6. Submission of Profile and Competency

Knowledge. This functionality supports uploading

of profile and competency knowledge from each

member organization. For each “piece” of

knowledge, the class of this knowledge needs to be

indicated in the VBE profile and competency sub-

ontology.

7. Viewing of Profile and Competency

knowledge. This functionality supports viewing the

profile and competency knowledge accumulated in

the VBE. The viewing scope shall address both:

single profile knowledge and the collective profile

knowledge of the entire VBE. The structuring of the

knowledge in the GUI (see Section 5 for more

details) shall mimic the VBE profile and

competency sub-ontology.

8. Matching/searching of Profile and

Competency Knowledge. This functionality

supports both: the search for specific profile

elements and the matching of the profile and

competency descriptions of a group of VBE member

organizations against the detailed descriptions of the

new collaborative opportunities arisen in the VBE.

In case there is no “direct” search results for some

specific knowledge classes, “alternative” results for

“other” knowledge classes shall be suggested, based

on the closeness of knowledge classes in the VBE

profile and competency sub-ontology.

9. Transmission of Profile and Competency

Knowledge. This functionality supports the

transition of VBE member organizations’ profile and

competency knowledge to a special format in order

to support its transmission to other VBEs, external

institutions, or further VBE-related activities in the

market and society.

10. Transmission of Core Profile and

Competency Model. This functionality supports

transmission of the customized core profile and

competency model of one VBE to the format of the

VBE core profile and competency sub-ontology in

order to support its usage by the R&D organizations

working on the evolution of the generic/core VBE

profile and competency model.

11. Transmission of Domain Classifications. This

functionality supports transmission of customized

generalization hierarchies of domain classes of one

VBE to the format of the VBE domain profile and

competency sub-sub-ontologies in order to support

its inheritance by other VBEs from the same domain

or by the R&D organizations working on the

evolution of these generalization hierarchies.

5 DATABASE SCHEMA AND

VISUAL INTERFACE

The design of the database for the VBE member

organizations’ knowledge aims to support both

structuring of members’ profiles/competencies based

on the VBE profile and competency sub-ontology,

and dynamic customization of the profile and

competency model, i.e. through dynamic

creation/deletion of knowledge classes and

instances. As the DBMS, the PostgreSQL

(PostgreSQL, 2007) has been initially chosen

because it represents a strong free-ware system, for

which the needed drivers and documentation are

available. A number of logical/physical database

designs have been considered and evaluated.

However, the approach, where one physical table in

the relational database corresponds to one class of

the profile knowledge has been rejected. The main

reason for the rejection is the need to support the

dynamic creation/deletion of database tables,

resulted from the requirement of dynamism in

profile knowledge classes. Such dynamic operations

with tables are however problematic in PostgreSQL.

Instead, we chose for a more object-oriented design

of the database with only one generic table for all

knowledge classes. Thus, all operations with classes

simply represent the operation with the records in

this table. The final database schema consists of

seven tables/relations (as illustrated in Figure 5).

The main four tables include: (a) the “class” table

for representing the profile knowledge classes; (b)

the “instance” table for representing the profile

knowledge instances (i.e. real data from VBE

entities); (c) the “class_relation” table for

representing different relationships among the

classes; and (d) the “instance_relation” table for

representing the relationships among the instances.

The other three tables are meta-data defined above

these four tables.

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Figure 5: Database schema.

Suitable user-friendly graphical user interface

of the profile and competency knowledge is required

to support their navigation, understanding and

“digestion” by human users. The more complex the

knowledge is the more difficult it is to specify

proper form for its visualization. Below we

introduce some “catalogue” forms for the profile

knowledge visualisation. Each catalogue mimics the

visualization of an acyclic graph including the

knowledge “classes” (representing both: core classes

and domain classes) and their “instances” as its

“nodes”, and three types of relationships as its

“edges”. These relationships include: (1) the

generalization relationship (called “has subclass”)

defining classes and their subclasses, (2) the

aggregation relationship (called “has attribute”)

defining classes and their attributes, and (3) the

instantiation relationship defining classes and their

instances. Two types of catalogues, namely the

PKCC and PKIC that are described below, are

designed for representing the VBE member

organizations’ profile and competency knowledge.

In relation to illustrations of PKCC and PKIC,

addressed in Figures 6 and 7, please notice that in

both catalogues described and illustrated below, the

bold entries represent knowledge classes. The

image

, located next to a class, indicates that this

class is a sub-class of its upper-level class. In the

PKCC, absence of this image next to a class

indicates that this class is an attribute of its upper-

level class. In the PKIC, the italicized entries

represent dome instance’s data for attributes, also

called “records”. The image

in the PKIC

indicates a record. In both catalogues, the smaller-

font entries next to the class entries, e.g. “14

attributes”, “2 subclasses”, “2 records”, represent the

summary for the class definitions. The clickable

images

and support expanding and collapsing

the catalogue items. A radio-button

next to each

entry supports the selection of an entry to perform

some operations on it (e.g. creation of a new

subclass, a new attribute, or a new instance).

The Profile Knowledge Class Catalogue (PKCC)

represents an acyclic graph including the profile

knowledge classes as the nodes, and the

relationships among these classes as the edges. The

root of PKCC is represented by an abstract class

called “Profile knowledge”. The relationships

among the classes represent two types of the “has

attribute” relationships (e.g. a competency definition

has a capability definition as an attribute) and the

“has subclass” relationships (e.g. the manufacturing

capability has the welding capability as a subclass).

An example illustration of the PKCC is addressed in

Figure 6. This Figure illustrates the list of the top-

level classes of profile knowledge such as “General

data”, “Contact data”, “Resource”, etc. The

representation of two classes, namely the “General

data” class and the “Resource” class are also

expanded, so that the fourteen attributes of the

“General data” class, as well as one attribute and

four sub-classes of the “Resource” class, can be

viewed.

Figure 6: An example illustration of PKCC.

Figure 7: An example illustration of PKIC.

The Profile Knowledge Instance Catalogue

(PKIC) represents an acyclic graph that includes the

profile knowledge classes and the profile knowledge

instances as the nodes, and the relationships among

these classes and instances as the edges. Please note

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319

that the relationships among classes in PKIC

represent only the “has subclass” type, the instances

are not connected among each other directly, while

the main types of the relationships in this models

represent the relationships between classes and their

instances. An example illustration of the PKIC is

addressed in Figure 7. This Figure illustrates a list of

classes for the profile knowledge and some existing

records for these classes from a member

organization of Swiss Microtech (SMT) - a VBE

from Switzerland. In this Figure, the record for the

“General data” is expanded, so that the records for

its attributes can be viewed, For example, the record

for the “Creation date” is “1956”. It also illustrates

that the “Resource” class does not have direct

instances/records, rather it has records only through

one of its sub-classes, e.g. through the “Human

resource” class.

6 CONCLUSIONS

This paper addresses an approach for ontology-

based modeling and management of characteristic

knowledge collected from organizations/companies

collaborating in CNOs and specially in VBEs. Each

organization is presented in VBEs by its “profile”

and specifically by its “competency” - a fundamental

element of the profile. This paper starts with the

definitions of organizations’ profiles and

competencies. It addresses the motivations,

requirements, and technical challenges for ICT-

based modeling and management of organizations’

profiles and competencies in VBEs. It introduces the

“VBE profile and competency sub-ontology” to

support modeling and management of organizations’

knowledge in VBEs. Furthermore, the functionalities

for profile and competency management are

presented that are based on the ontological

representation of the organization’s knowledge

model. As steps required for specification and

development of the Profile and Competency

Management System (PCMS) for VBEs, the designs

of both: the database and the GUI for profile and

competency knowledge, are addressed. More details

about specification and modeling of organizations’

competencies as well as about the PCMS’s

development fall outside the scope of this paper, and

are the topics for forthcoming papers.

ACKNOWLEDGEMENTS

The work on this paper is supported in part by the

FP6 IP project ECOLEAD, funded by the European

Commission.

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