Submitted By - Cochin University of Science and Technologydspace.cusat.ac.in/jspui/bitstream/123456789/3613/1/KN_report.pdf · Knowledge Network Submitted By ... 5.6 Nonaka's Model

Knowledge Networks

1 Department Of Computer Science

COCHIN UNIVERSITY OF SCIENCE AND TECHNOLOGY

COCHIN – 682022

2010

Seminar Report

On

Knowledge Network

Submitted By

Hafsath.C.A

In partial fulfillment of the requirement for the award of

Degree of Master of Technology (M.Tech)

In

Software Engineering

Knowledge Networks


DEPARTMENT OF COMPUTER SCIENCE

COCHIN UNIVERSITY OF SCIENCE AND TECHNOLOGY

COCHIN – 682022

Certificate

This is to certify that the Seminar report entitled ″Knowledge Network″,

submitted by Hafsath.C.A, Semester I, in the partial fulfillment of the requirement for the award of

M.Tech. Degree in Software Engineering is a bonafide record of the Seminar presented by her in

the academic year 2010.

Dr. Sumam Mary Idicula Dr. K Paulose Jacob

Seminar Guide Head of the Department

Knowledge Networks


ACKNOWLEDGEMENT

I express our profound gratitude to the Head of Department Dr. K

Paulose Jacob for allowing me to proceed with the seminar and also for giving me full freedom to

access the lab facilities.

My heartfelt thanks to my guide Dr. Sumam Mary Idicula for taking

time and helping me through my seminar. She has been a constant source of encouragement without

which the seminar might not have been completed on time. I am very grateful for her guidance.

I am also thankful to Mr.G Santhosh Kumar, Lecturer, Department of Computer

Science, for helping me with my seminar. His ideas and thoughts have been of great importance.

Knowledge Networks


ABSTRACT

The world is experiencing an era which is termed as “knowledge age”. In this new context,

knowledge is the primary commodity and management of knowledge becomes more and more

crucial. Knowledge network is an effective method for knowledge management. KN is a method

used for combining individual’s knowledge and skills in pursuit of personal and organizational

objectives. Knowledge network is grounded not just the application of existing explicit

knowledge, but the sharing of tacit and implicit knowledge.

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CONTENTS

1. Introduction………………………………………………………

2. Information hierarchy…………………………………………….

3. Knowledge? …………………………………………………………

4. Knowledge management…………………………………………..

5. Knowledge network…………………………………………………

5.1 Need?.................................................................................

5.2 Operating principles………………………………………..

5.3 Structure……………………………………………………..

5.4 Components…………………………………………………..

5.5 Process………………………………………………………

5.6 Nonaka's Model of Knowledge Creation & Transformation…

5.7 Layers………………………………………………………..

5.8 Components of success………………………………………

5.9 Case study……………………………………………………

6. Conclusion………………………………………………………

7. References……………………………………………………..

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1. Introduction

Over the last three decades the use of computers has steadily changed along the

spectrum from aiding computation (data processing) to communications (email etc.). It is now

entering a new era of helping cognition - human thinking and knowledge processes. However

much information organizations store in computer only a small fraction of the knowledge needed

to run an enterprise is encapsulated in this form or in manual procedures - 10%-30% is the figure

given by most groups asked to estimate this percentage. The rest is the tacit knowledge and

wisdom in people's heads.

Tacit knowledge becomes even more important in a dynamic business environment and

is the key to an organization’s ability to respond in a flexible and timely manner. This is a role that

knowledge networking can help fill.

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2. Information hierarchy

The content of the human mind can be classified into five categories:

1. Data: Data is raw. It simply exists and has no significance beyond its existence (in and of

itself). It can exist in any form, usable or not. It does not have meaning of itself. In computer

parlance, a spreadsheet generally starts out by holding data.

2. Information: Data that are processed to be useful; provides answers to "who", "what",

"where", and "when" questions information is data that has been given meaning by way of

relational connection.

3. Knowledge: Application of data and information; answers "how" questions. Knowledge is

the appropriate collection of information, such that it's intent is to be useful. Knowledge is a

deterministic process.

4. Understanding: Appreciation of "why”. Understanding is an interpolative and probabilistic

process. It is cognitive and analytical. It is the process by which I can take knowledge and

synthesize new knowledge from the previously held knowledge. The difference between

understanding and knowledge is the difference between "learning" and "memorizing".

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5. Wisdom: evaluated understanding. Wisdom is an extrapolative and non-deterministic, non-

probabilistic process. It calls upon all the previous levels of consciousness, and specifically

upon special types of human programming (moral, ethical codes, etc.).

3. Knowledge

Knowledge is the knowing familiarity gained by experience; person’s range of

information; a theoretical or practical understanding of; the sum of what is known.

There are three types of knowledge:

i) Explicit knowledge

ii) Tacit knowledge

iii) Implicit knowledge

Explicit knowledge is that which is written down, recorded or codified in some manner

is often used almost interchangeably with information in the knowledge management /knowledge

network context. The mapping and sharing of knowledge focuses primarily on individual explicit

knowledge and its relation to organizational explicit knowledge.

Tacit knowledge is the understanding of how to do things. It is created by doing, by

personal trial, error, reflection and revision ie. Understanding how to research and develop new

policy recommendations, learning how to run a community consultation or how to negotiate a

policy change with a decision-maker. But it is difficult to articulate what that

“how to” actually is. The transfer of tacit knowledge is, therefore, through shared processes

ie.working together, mentoring, and so forth in addition to the physical transmission of written or

recorded content.

Finally, implicit knowledge refers to an individual’s “contextual surroundings … that

are imbued with and shape his collective values, normative behavior, roles, customs, and

expectations of events” in short, an individual's culture and values.

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4. Knowledge management

In an economy where the only certainty is uncertainty, the one sure source of

lasting competitive advantage is knowledge.” This change of focus forces organizations to re-think

the way they manage their business since the focus is no longer on tangible assets but on people’s

abilities and experience. In the industrial economy if people thought about knowledge at all they

operated from the old equation: knowledge is power, so hoard it. Today companies are embracing a

new equation for success: knowledge is power, so share and it multiplies. This new logic represents

a radical rethinking of basic business and economic models.

Knowledge-focused strategic domains:

• Sharing knowledge and best practices

• Instilling responsibility for sharing knowledge

• Capturing and reusing past experiences

• Embedding knowledge in product, services and processes

• Producing knowledge as a product

• Driving knowledge generation for innovation

• Mapping networks of experts

• Building and mining customer knowledge bases

• Understanding and measuring the value of knowledge

• Leveraging intellectual assets

Such focus areas are typical of companies that embrace the sharing of

knowledge across organizational boundaries. Corporate know-how is important at strategic levels

to sense the environment and challenge management assumptions. At the tactical level, day-to-day

decision making requires that people talk candidly, share their experience and insights, and find

meaning together. At the operational level, replicating best practices throughout the company

Knowledge Networks


quickly and effectively can lead to greater efficiencies, lower costs and higher quality of goods and

services.

Two main streamlines of knowledge management focus on different approaches:

Information Management Personnel Management

Knowledge network is an effective method for knowledge management which

integrate these two approaches

Knowledge as network IT network Use and reuse of

knowledge

Knowledge as process Social network Creation of knowledge

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5. KNOWLEDGE NETWORK

Knowledge network is described by Newman. KN mainly for interactive knowledge

creation and use. Interdisciplinary communities can share knowledge and build knowledge for

complex problems .It uncovering expertise within the organization and connections to/with

external contacts. Basically it is a set of relationships. It is more focused and narrowly based than

informal network. It is an effective way of combining individuals’ knowledge and skills in pursuit of

personal and organizational objectives.

5.1 Need The Web has become an indispensable tool of modern culture. To a degree, its

initial promise of creating a global network that offers access to the knowledge of the world has

been realized. It supports advanced technological research in the sciences, arts, and humanities, but

it also has popular appeal (online news, media, telecommunications) and has drawn wide public

engagement (Flickr, Wikipedia). Powerful, but relatively crude, search engines organize the

enormous amount of information on the Internet into simple answers to clear cut, search term-based

questions. What is deceptive about this everyday process is that it flattens rather than deepens and

improves knowledge since popular search engines enforce a historical perspective; the Web does not

support the long-tail effect.

5.2 Operating principles Knowledge networks consist of groups of expert institutions working together on a

common concern, strengthening each other's research and communications capacity, sharing

knowledge bases and developing solutions that meet the needs of target decision

Based on this definition, there are several operating principles for formal networks:

1. Knowledge networks are purpose driven.

We have observed that the narrower the focus, the more influential a network

becomes. The institutional collaboration takes place around a single issue or problem rather than a

broad spectrum of interests. Focus is essential. The network's research on the issue should be

Knowledge Networks


transdisciplinary. The purpose of the network could be thematically based (ex. trade,

dams, ozone depletion) or regionally focused (ex. environmental policy options in Central America).

2. Knowledge networks are working networks.

One of the greatest challenges in setting up and running a network is moving the

participants beyond basic information exchange to actually working together on solutions. In our

view, knowledge networks are far more "work" than "net.”? A working network is driven not just

by research but by implementation. As part of creating work plans for the network, the members

should focus on how the results of the network's research will be used. The work plans should

include strategies for the application of the research: How will the research be linked to the public

policy process? How will the process or technology developed by the network be commercialized

or put into practice by those outside the network?

3. Knowledge networks require institutional commitment beyond the participation of

individuals and experts.

While expert networks and consultative groups have their place, we have learned

that a knowledge network requires the commitment of an institution for several reasons.

Accountability: The participants in the network represent institutional

mandates rather than personal research interests. The agenda is, therefore, more

likely to be focused on implementation. Participants are also held accountable for

their work not only by their colleagues in the network, but by the institutions they

represent.

Continuity: Networks can take up to a decade to thrive and have real impact. With

institutional commitment, it is more likely that work will continue even if individual

staff changes.

Commitment of resources: The network activities will be endorsed as part of each

institution's mandate, making easier the justification of both financial and in-kind

support from participating institutions and ensuring their involvement in promoting

the results of the network's research. 4. Knowledge networks are built on expertise, not just interest alone.

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The identification and selection of members is one of the most important tasks of the

network. The reputation of the network, and the level of influence it will have, will be based on the

expertise and credibility of the members. We also suggest, as guiding principle, that institutional

membership be based on expertise and the capacity to undertake the research and implement work

plans. Interest in an issue is not, in itself, reason enough to include an organization in a knowledge

network.

Membership in a formal network should be based on merit. In order for a knowledge

network to create new knowledge and to have real influence, that knowledge and influence must be

grounded in expertise and reputation. If exclusivity is a concern of the network, then

communications mechanisms can be employed to bring points of view from outside of the

immediate network membership. These include workshops, electronic conferences, the nomination

of associate members for specific activities and the formation of more open, dynamic "working

groups" within the formal network.

5. Knowledge networks are cross-sectoral and cross-regional.

Knowledge networks should result in a reduction of boundaries between sectors such

as universities and industry, or governments and civil society.

6. Knowledge networks must develop and strengthen capacity in all members.

Strengthening capacity is critical to the formal knowledge network model: we create

knowledge networks in order to learn from each other and build on each other’s strengths. Capacity

development occurs at all points in the work plan: in research management; in the substantive

issues; in virtual teamwork; in communicating findings more broadly; and in influencing decision-

making. An underlying premise of a knowledge network is that the whole is greater than the sum of

the parts. However, a significant benefit of participating in a knowledge network is that each of the

parts becomes stronger.

7. Knowledge networks are communications networks.

This final principle underpins all the others. The knowledge created and

aggregated by the network must be shared beyond the network members. This operating principle is

part and parcel of a network being a purpose-driven, working network. Mechanisms must be put in

place from the beginning to reach targeted decision-makers who will be the ones to put the research

of the network into action.

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5.3 Structure of Knowledge network When people think about some things or events, all the concepts (nodes) are

connected by some relations or Laws (links) to formulate a network. The network can be used as a

thinking and knowledge presentation tool .For a working group, the concepts of all members with

different expertise will be integrated as a large network

There are three kinds of linking in the knowledge network system:

1. Linking knowledge to knowledge: The different units of knowledge can be linked. It is

the necessary condition for the knowledge integration.

2. Linking people to knowledge: This is the important way for people to get the knowledge.

and In reverse direction users can find the related people from the knowledge.

3. Linking people to people. This forms a social network.

5.4 Components of Knowledge Network Knowledge architecture can be regarded as a prerequisite to knowledge sharing.

The infrastructure can be viewed as a combination of people, content, and technology.

The People Core

By people, here we mean knowledge workers, managers, customers, and suppliers. As

the first step in knowledge architecture, our goal is to evaluate the existing information/ documents

which are used by people, the applications needed by them, the people they usually contact for

solutions, the associates they collaborate with, the official emails they send/receive, and the

database(s) they usually access. All the above stated resources help to create an employee profile,

which can later be used as the basis for designing a knowledge management system. The idea behind

assessing the people core is to do a proper job in case of assigning job content to the right person

and to make sure that the flow of information that once was obstructed by departments now flows

to right people at right time.

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The Technical Core

The objective of the technical core is to enhance communication as well as ensure

effective knowledge sharing. Technology provides a lot of opportunities for managing tacit

knowledge in the area of communication. Communication networks create links between necessary

databases. Here the term technical core is meant to refer to the totality of the required hardware,

software, and the specialized human resources. Expected attributes of technology under the

technical core: Accuracy, speed, reliability, security, and integrity. Since an organization can be

thought of as a knowledge network, the goal of knowledge economy is to push employees towards

greater efficiency/ productivity by making best possible use of the knowledge they posses.

Content core Knowledge stored in the database Procedures Access, Navigation, Observation, Analysis, Collaboration, Learning

5.5 Process in KNS

The knowledge network system aims at the integration all the knowledge resources at

all the levels (as well as the whole Internet) and provides easy and flexible means for the knowledge

capturing, processing, and creation. In the daily work, people get their knowledge through the

following ways: Searching and finding knowledge on paper (explicit knowledge). Meeting persons

in real life to get explicit and tacit knowledge. Using multimedia communication tool like telephone,

TV to get some knowledge. From personal computer, in which there exist some knowledge

captured and stored .From the distributed knowledge network (DKN) at different level. Creating

new knowledge after capturing, integrating existing knowledge and creative mental process .For the

effective processing the knowledge, the concept of knowledge node is introduced. A knowledge

node is a kind of high level processing unit. It has three main functions:

1. Dissemination of information on request or automatically channelled.

2. Two way communication and feedback capacities through multimedia interfaces.

3. Access to a local knowledge bank and possibly meta knowledge about other knowledge

nodes.

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At the lowest level, a technological innovation is preceded by a number of

interconnected scientific and technological facts (concepts). In the basic research work, those

facts may present new scientific ideas, theories, empirical achievements, discoveries, etc in

different scientific disciplines. In applied research work, they are advances in different

technologies, e.g. new technical solutions, inventions, new principles and methods of design and

manufacturing, etc. A network can be constructed by connections between these facts or concepts.

Each node can be interlinked to another node at different levels

The more important point is each new concept may play a catalytic role in triggering

out new ideas and their applications to extending knowledge. If we can mine the existing

networks and explore some pieces of network and integrate them, some prototypes of knowledge

generating network may be expected, though it can not guarantee to perfect success. The most

crucial task for the knowledge management is knowledge conversion and creation. A typical

approach is put forward by Nonaka and Takeuchi. They assumes that knowledge is created

through the interaction between tacit and explicit, individual and organizational knowledge, and

proposes four modes of knowledge conversion.

5.6 Nonaka's Model of Knowledge Creation & Transformation

In 1995, Nonaka coined the terms tacit knowledge and explicit knowledge as the

two main types of human knowledge. The key to knowledge creation lies in the way it is mobilized

and converted through technology.

Tacit to tacit communication (Socialization): Takes place between people in meetings or in

team discussions.

Tacit to explicit communication (Externalization): Articulation among people trough

dialog (e.g., brainstorming).

Explicit to explicit communication (Communication): This transformation phase can be

best supported by technology. Explicit knowledge can be easily captured and then

distributed/transmitted to worldwide audience.

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Explicit to tacit communication (Internalization): This implies taking explicit knowledge

(e.g., a report) and deducing new ideas or taking constructive action. One significant goal of

knowledge management is to create technology to help the users to derive tacit knowledge

from explicit knowledge.

5.7Layers of KNS The knowledge network system composed of 5 layers

1. User interface layer

2. Authorized Access Layer

3. Collaborative Intelligence and Filtering Layer

4. Knowledge-Enabling Application Layer (Value-Added Layer)

5. Transport Layer

6. Middleware Layer

7. Repositories Layer

User Interface layer

It is the top layer in the KM system architecture. A web browser represents the

interface between the user and the KM system.It provide a way for the proper flow of tacit and

explicit knowledge ie, Capturing tacit knowledge from experts and making it available to people

User interface layer should have following features:consistency, relevancy ,visual clarity ,usability

,ease of navigation

Authorized Access Layer

This layer maintains security as well as ensures authorized access to the knowledge

captured and stored in the organization's repositories. The knowledge is usually captured by using

internet, intranet of extranet. An organization's intranet represents the internal network of

communication systems. Extranet is a type of intranet with extensions allowing specified people

(customers, suppliers, etc.) to access some organizational information. Issues related to the access

layer: access privileges, backups. The access layer is mostly focused on security, use of protocols

(like passwords), and software tools like firewalls.

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Firewalls can protect against:

E-mails that can cause problems.

Unauthorized access from the outside world.

Undesirable material (movies, images, music etc).

Unauthorized sensitive information leaving the organization.

Firewalls can not protect against:

Attacks not going through the firewall.

Viruses on floppy disks.

Weak security policies.

Collaborative Intelligence and Filtering Layer

This layer provides customized views based on stored knowledge. Authorized users

can find information (through a search mechanism) tailored to their needs. Intelligent agents (active

objects which can perceive, reason, and act in a situation to help problem solving) are found to be

extremely useful in some situations. In case of client/server computing, there happens to be frequent

and direct interaction between the client and the server. In case of mobile agent computing, the

interaction happens between the agent and the server. A mobile agent roams around the internet

across multiple servers looking for the correct information.

Some benefits can be found in the areas of:

Fault tolerance.

Reduced overall network load.

Heterogeneous operation.

Key components of this layer: The registration directory that develops tailored

information based on user profile. Membership in specific services, such as sales promotion, news

service etc. The search facility such as a search engine. In terms of the prerequisites for this layer,

the following criteria can be considered: Security, Portability, Flexibility, Scalability, Ease of useand

Integration.

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Knowledge-Enabling Application Layer (Value-Added Layer)

This creates a competitive edge. Most of the applications help users to do their jobs

in better ways. They include knowledge bases, discussion databases, decision support etc.

Transport Layer

This is the most technical layer. It ensures to make the organization a network of

relationships where electronic transfer of knowledge can be considered as routine. This layer

associates with LAN (Local Area Network), WAN (Wide Area Network), intranets, extranets, and

internet. In this layer we consider multimedia, URL's, connectivity speeds/bandwidths, search tools,

and consider managing of network traffic.

Middleware Layer

This layer makes it possible to connect between old and new data formats. It

contains a range of programs to do this job.

Repositories Layer

It is the bottom layer of the KM architecture which represents the physical layer in

which repositories are installed. These may include, legacy applications, intelligent data

warehouses, operational databases etc. After establishing the repositories, they are linked to form

an integrated repository.

5.8Components for success We have found that effective formal knowledge networks usually have certain

components, some of which are well-understood and have been extensively documented and others

which are less well-understood or previously uninvestigated

1. External communications and engagement strategies for network audiences

According to our principles, knowledge networks need to be purpose driven,

workingnetworks, and they must be communications networks. This means that the knowledge

created by the network must be for broader application outside of the network. There are two levels

of audience for networks: the target audience - those whom the network most wants to influence

with the outputs of its work broader audiences - those individuals and organizations interested in

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or working on the same issues as the network. Each network should continually ask what impact it

hopes to have and on whom. The participants should determine their target audience with as much

specificity as possible. The network should consider how it will move its advice and solutions into

practice.

2. Relationship building, management and governance

It explores the need for setting network goals and objectives (the"purpose" or

focus of the network), network membership issues, governance and decision-making mechanisms,

day-to-day management through a secretariat or coordinating unit, funding and resource sharing

issue. The network falls into disuse without institutional commitment and staffing to continually

push all of the participants. The opportunity to develop new policy recommendations and new

development practices would be lost without this level of attention

3. Internal communications infrastructure and virtual teamwork protocols

For members to learn from each other and build on each other’s strengths,

knowledge networks require a communications infrastructure and protocols to support the joint

work of network members. An important step in managing a knowledge network is the creation of a

private, closed “extranet” to link the network members.

4. Evaluation mechanisms

It is a common observation that what you can't measure, you can't manage. More

research on measuring the overall performance of knowledge networks is required in order to

manage them more effectively. We think that pooling our knowledge and staff resources in a

knowledge network may result in more cost-effective research, particularly when adequately

supported by information and communications technologies.

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5.9 Case study

1. Halliburton energy services, Texas started a number of knowledge networks as part of

knowledge management implementation

Let us assume that a user has a question. The user performs a self-search and

looks in the Knowledge Repository for relevant information. If the user cannot find what she/he

needs in the repository, then she/he posts the issue on the collaboration tool in the community

portal. The community members can contribute suggestions, share experiences, and help clarify the

scope of the problem until a solution is found. The community of practice has a full-time

“Knowledge Broker” (KB) who connects those who know with those who need to know. An

important part of developing the community is identifying individuals around the globe who have

specific expertise. The Knowledge Broker then connects those individuals with expertise to those

within the community who need it. Once solutions are validated by a subject matter expert (SME)

and acknowledged as a viable solution by the user, the KB tags the solution with taxonomy

attributes and metadata and places it in the knowledge repository for further use.

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Another component of the community learning system not apparent in the

processes described above is ‘learning on demand’. As users access the community portal, there are

new issues and questions posted to the collaboration tool daily. Users learn by reading the postings,

comments and solutions of others, as well as their own. The collaboration postings and threaded

discussions are a rich source of knowledge and information, and can be searched using the portal

search tool. Users do not have to wait until this posting is placed in the knowledge repository to

have access to it.

2. Knowledge network of Infosys solutions

Main co mponents of the system are:

KM portal: a central repository for contents

People knowledge map: a directory service for locating experts

Knowledge exchange: a set of online discussion forums

K-mail: an auto response generator and work flow engine for answering questions

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6. Conclusion

www flattens rather than deepens and improve the knowledge,butKnowledge

network concentrate on knowledge than raw information. The Cabinet Committee on Infrastructure

has accorded in principle approval for the establishment National Knowledge Network (NKN).The

knowledge network is planned to be implemented by the NIC and will inter-connect all knowledge

institutions trough high speed data communication network.NKN would encourage sharing of

knowledge, specialized resources and collaborative research among scientists, researchers and

students from diverse spheres across the country to work together for advancing human

development in critical and emerging areas.NKN will catalyze knowledge sharing and knowledge

transfer between stakeholders seamlessly– that too across the nation and globally for creating

intellectual property.NKN would enable use of specialized applications and allow sharing of high

performance computing facilities, e-libraries, virtual classrooms and very large databases.

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7. References

1. Martin Doerr,The dream of a global knowledge network-Anew approach:

http://portal.acm.org/citation.cfm?id=1367080.1367085

2. Heather Creech,Principles for sustainable development Knowledge networks:

http://docs.google.com/viewer?a=v&q=cache:_fY481Qhh4sJ:www.iisd.org/pdf/2001

/networks_operating_principles.pdf

3. Verna Alle,Knowledge network and community of practices:

http://docs.google.com/viewer?a=v&q=cache:YRej8SHjv9AJ:www.vernaallee.com/

value_networks/KnowledgeNetworksAndCommunitiesOfPractice-28Jan07.pdf

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Submitted By - Cochin University of Science and Technologydspace.cusat.ac.in/jspui/bitstream/123456789/3613/1/KN_report.pdf · Knowledge Network Submitted By ... 5.6 Nonaka's Model