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What Knowledge Management can learn from eScience & Education Knowledge and the management of knowledge Dr. L.A. Plugge
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eScience, Education and Knowledge Management

Oct 21, 2014

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What Knowledge Management can learn from eScience & Education
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Page 1: eScience, Education and Knowledge Management

What Knowledge Managementcan learn from

eScience & EducationKnowledge and the management of knowledge

Dr. L.A. Plugge

Page 2: eScience, Education and Knowledge Management

Competing and Collaborating for the Future

2

You have added much several ways.If I have seen further, it is by standing on the shoulders of Giants.

Written by Isaac Newton in a letter to Robert Hooke, 5 feb. 1676

Page 3: eScience, Education and Knowledge Management

Topics

• SURF as facilitator and innovator for education and research

• What is knowledge?

• What is Knowledge Management (not)?

• Academic knowledge strategy

• How ICT changes research and education

3

Page 4: eScience, Education and Knowledge Management

SURF

SURF is the higher education and research partnership organization for network services and information and communication technology (ICT).

SURF participants:

14 universities45 universities for professional education5 research institutions

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SURF – innovation & services

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Scientific Technical Council (WTR)

• Independent Council of SURF

• 12 Council members (max)

• Appointed on personal merits

• Term 3 years (extension possible)

• Provides advice for SURF and its member

institutions, either on request or on its own

initiativewww.surf.nl/wtr

Page 7: eScience, Education and Knowledge Management

Innovation Method (1)

• Provide vision in 4-year Strategic Plan(Scientific Technical Council)

• Commitment of the institutions for HE.Membership fees

• Execute the Strategic Plan, Based on Policy Considerations of the Government

• Monitor and assess progress of innovation projects(Project Monitoring Committee)

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Page 8: eScience, Education and Knowledge Management

Innovation Method (2)

Technological

scouting

2 3 4 51

Services

develop-ment

Assessment

studies

Production

Marketing

Fasingout

Technologicaldevelopment

Clientneeds

Plan for TA Business case Business plan

Marketing plan PlanFasing out

service

Plantermination

service

Feedback

Life cycle phases

External Developments

InventoryClient needs

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Page 9: eScience, Education and Knowledge Management

Areas of competition and collaboration

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Edwards & PeppardCranfield School of Management

Common industry processes

Essential and unique to the organization type

Processes to outperform the

competition

Provide futureRequired competences

Page 10: eScience, Education and Knowledge Management

Strategic Plans of SURF since 1986

1986-1990 To a common network: SURFnet 1 - 9.6 Kbit/sec

1991-1994 Communication services, Software Licences

1995-1998 Innovation of administrative systems in institutions

1999-2002 Innovation in Education

2003-2006 Cooperation between institutions in administrative systems

2007-2010 Services Oriented Approach

2011-2014 (Cloud) infrastructure and services for education & research

1010

Page 11: eScience, Education and Knowledge Management

Topics

• SURF as facilitator and innovator for education and research

• What is knowledge?

• What is Knowledge Management (not)?

• Academic knowledge strategy

• How ICT changes research and education

11

Page 12: eScience, Education and Knowledge Management

Mathieu Weggeman12

Page 13: eScience, Education and Knowledge Management
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In other words:

Knowledge is constructed and represented in our brain.

The question is

Can we represent knowledge

outside our brain?

Do documents contain knowledge?

Page 17: eScience, Education and Knowledge Management

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Paper Disk

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Goal of knowledge representation

• Securing knowledge, outside humans

• Making it available to others

• Making knowledge less scarce

• Automate the creation of new knowledge

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Artificial Intelligenceand

knowledge representation

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Knowledge representation in rule based expert systems

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Facts

RulesInferenceEngine

UserInterface

Page 22: eScience, Education and Knowledge Management

The Paris Hilton Problem

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Some limitations ofknowledge systems

• Knowledge is represented in symbols

• Procedurele knowledge is represented in rules

• Conceptual knowledge is represented data

• “Brittleness”

• “Halting” problem

• “Grounding” problem

• How to define the knowledge boundaries?

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Page 25: eScience, Education and Knowledge Management

Knowledge representation in Neural Networks

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Page 26: eScience, Education and Knowledge Management

Current ‘knowledge representation’ still lacks:

• (deep) Understanding

• Creativity

• Intuition

• Fascination

• Ingenuity / originality

• Creativity

• …

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Page 27: eScience, Education and Knowledge Management

Explicit and Implicit knowledge

• Explicit knowledge

−Can be coded−Transferable−Copyable

• Implicit knowledge

−Transferable, in principle…

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Page 28: eScience, Education and Knowledge Management

Implicit knowledge:Students versus Expertsdiagnosing patients

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6

0

8 97

33

chaoticagressive

depressive

14

13 72

chaoticagressive

depressive

Page 29: eScience, Education and Knowledge Management

Explicit - Implicit• Implicit knowledge is just as important as explicit

knowledge

• Transfer of implicit knowledge takes time and physical presence

Examples from learning:− to drive a car− to play a music instrument− how to perform open heart surgery− Bread baking machine…

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Page 30: eScience, Education and Knowledge Management

Topics

• SURF as facilitator and innovator for education and research

• What is knowledge?

• What is Knowledge Management (not)?

• Academic knowledge strategy

• How ICT changes research and education

30

Page 31: eScience, Education and Knowledge Management

Knowledge managementis creating opportunitiesthrough strategies and practicesfor Knowledge Creationand Knowledge Transfer

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Nonaka’s & Takeuchi’s Theory on Knowledge Creation, 1995

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Knowledge exchange = Communication

SoundText

VideoVideo & Sound

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What is the essence of

34

Lascaux (13 000 v. C.)Library of Congress

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Knowledge management process

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Create Capture Organise Access Use

KnowledgeCreation

KnowledgeApplication

Knowledge Sharing

Page 36: eScience, Education and Knowledge Management

Topics

• SURF as facilitator and innovator for education and research

• What is knowledge?

• What is Knowledge Management (not)?

• Academic knowledge strategy

• How ICT changes research and education

36

Page 37: eScience, Education and Knowledge Management

Academia and knowledgeAcademia

the community of students and scholars

engaged in higher education and research;

the cultural accumulation of knowledge,

its development and transmission.

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Tony Hey, Stewart Tansley, and Krist in Tolle, The fourth paradigm, 2009

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Mathieu Weggeman39

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Academic knowledge transfer (1)

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HypothesisMethodResults

Conclusions submitpublisher

revise

Scientificworld

Research group / Individual Reviewers

producejudge

publish

Page 41: eScience, Education and Knowledge Management

Lineair view of scholarly communication

Page 42: eScience, Education and Knowledge Management

Tony Hey, Stewart Tansley, and Krist in Tolle, The fourth paradigm, 2009

Back to the e-Science Paradigm

Page 43: eScience, Education and Knowledge Management

Topics

• SURF as facilitator and innovator for education and research

• What is knowledge?

• What is Knowledge Management (not)?

• Academic knowledge strategy

• How ICT changes research and education

43

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X-informatics & computational Xdata intensive science

25-50% of the experimental budgets are for SOFTWARE

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What is e-Science about?

e-Science is not a new scientific discipline but a new method of knowledge development and exchange

e-Science is a the set of tools and technologies required to support collaborative, networked science.

e-Science is about the multidisciplinary analysis of data

e-Science is infrastructure to empower scientists to do their research in faster, better and different ways

(Based on Hey 2006)46

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eScience is facilitated by merging technologies

GT: grid technologyOGSA: open grid services architectureWSDL: web service definition languageWSDM: web services distribution management

Bob Hertzberger

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Technology facilitates a knowledge driven research infrastructure

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The network

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Netherlands e-Science Center

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Providing the opportunity to share and reuse

Bob Hertzberger 51

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Sharing, using and contributing to infrastructure

Bob Hertzberger

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Development of new technologyM

atu

rity

Hans Dijkman

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Page 54: eScience, Education and Knowledge Management

Effects of GigaPort NG Network innovation

Generic ICT-application

services

ICT-applications

Research Pilots Market

Networkinfrastructure GigaPort Next Generation

Network ProjectEffects telecommarket

Effe

cts

on

res

ea

rch

Inn

ova

tion

effe

cts

Primairy effects GigaPort

Secundairy effects GigaPort

Appliedinnovation

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Effects on consumer IT:the industrialization of IT

Ground floor: 56 containersOne container:  1800 to 2500 servers>100.000 servers

 Microsoft Data Center Chicago

Google Data Center Eemshaven

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Levels of IT services

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f.e. 1423 Repositories worldwide holding over >20.9 Million items

Repository66.org Repository Maps

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…and an increasing number of Services…

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… provided by suppliers in the cloud.

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The Internet has become a nervous system connecting and augmenting our brains…

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Scientific & Educational methods can help Knowledge Management to create opportunities to use and expand our knowledge.