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What Knowledge Managementcan learn fromeScience & Education Knowledge and the management of knowledge Dr. L.A. Plugge
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
Topics SURF as facilitatorand innovator foreducationand research What is knowledge? What is Knowledge Management (not)? Academicknowledgestrategy How ICT changes research and education 3
SURF SURF is the higher education and  research partnership organization for network services and information and communication technology (ICT). SURF participants: 14 universities 45 universities for professional education 5 research institutions
SURF – innovation & services 5
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 initiative www.surf.nl/wtr
InnovationMethod (1) ,[object Object],(Scientific Technical Council) ,[object Object],Membership fees ,[object Object],Based on Policy Considerations of the Government ,[object Object],(Project Monitoring Committee) 7
InnovationMethod (2) Life cycle phases 2 3 4 5 1 Technological scouting Services     develop-ment Assessment studies Production Marketing    Fasing out Technological development Client needs Inventory Client needs External Developments Plan for TA Business case  Business plan Marketing plan Plan Fasing out service Plan termination service Feedback 8
Areas of competitionandcollaboration Processes to outperform the competition Provide future Required competences Essential and uniqueto the organization type Common industry processes Edwards & Peppard Cranfield School of Management 9
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 10 10
Topics SURF as facilitatorand innovator foreducationand research What is knowledge? What is Knowledge Management (not)? Academicknowledgestrategy How ICT changes research and education 11
Mathieu Weggeman 12
14
In other words: Knowledge is constructed and represented in our brain. The question is  Can we represent knowledge outside our brain? Do documents containknowledge?
17 Paper Disk
Goal of knowledge representation Securing knowledge, outside humans Making it available to others Making knowledge less scarce Automate the creation of new knowledge 18
Artificial Intelligenceandknowledge representation
Knowledge representation in rule based expert systems 20 Inference Engine User Interface Rules Facts
Searle’s Chinese room Part 3 Part 4 21
The Paris Hilton Problem
IBM’s Watson The Match Day 1
Some limitations ofknowledge systems Knowledge is represented in symbols Procedurele knowledge is represented in rules Conceptualknowledge is represented data “Brittleness” “Halting” problem “Grounding” problem How todefine the knowledge boundaries? 24
Knowledge representation in Neural Networks 25
Current ‘knowledge representation’ still lacks: (deep) Understanding Creativity Intuition Fascination Ingenuity / originality Creativity … 26
Explicit and Implicit knowledge Explicit knowledge Can be coded Transferable Copyable Implicit knowledge Transferable, in principle… 27
28 depressive 14 2 13 7 agressive chaotic Implicit knowledge:Students versus Expertsdiagnosing patients depressive 6 0 3 3 8 9 7 agressive chaotic
Explicit - Implicit Implicitknowledge is just as important as explicit knowledge Transfer of implicitknowledge takes time andphysicalpresence Examplesfromlearning: to drive a car toplay a music instrument howtoperform open heartsurgery Breadbaking machine… 29
Topics SURF as facilitatorand innovator foreducationand research What is knowledge? What is Knowledge Management (not)? Academicknowledgestrategy How ICT changes research and education 30
Knowledge managementis creating opportunitiesthrough strategies and practicesfor Knowledge Creationand Knowledge Transfer
Nonaka’s & Takeuchi’s Theory on Knowledge Creation, 1995
Knowledge exchange = Communication Sound Text Video Video & Sound
What is the essence of 34 Lascaux (13 000 v. C.) Library of Congress
Knowledge management process 35 Create Capture Organise Access Use Knowledge Creation Knowledge Application Knowledge Sharing
Topics SURF as facilitatorand innovator foreducationand research What is knowledge? What is Knowledge Management (not)? Academicknowledgestrategy How ICT changes research and education 36
Academia and knowledge Academia ,[object Object],	engaged in higher education and research; ,[object Object],	its development and transmission. 37
Tony Hey, Stewart Tansley, and Krist in Tolle, The fourth paradigm, 2009
Mathieu Weggeman 39
Academic knowledge transfer (1) 40 revise Hypothesis Method Results Conclusions publisher submit judge produce publish Scientific world Reviewers Research group / Individual
Lineair view of scholarlycommunication
Tony Hey, Stewart Tansley, and Krist in Tolle, The fourth paradigm, 2009 Back to the e-Science Paradigm
Topics SURF as facilitatorand innovator foreducationand research What is knowledge? What is Knowledge Management (not)? Academicknowledgestrategy How ICT changes research and education 43
44
X-informatics & computational Xdata intensive science 25-50% of the experimental budgets are  for SOFTWARE
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
eScience is facilitated by merging technologies GT: grid technology OGSA: open grid services architecture WSDL: web service definition language WSDM: web services distribution management Bob Hertzberger 47
Technology facilitates a knowledge driven research infrastructure 48
The network 49
Netherlands e-Science Center 50
Providing the opportunity to share and reuse Bob Hertzberger 51
Sharing, using and contributing to infrastructure Bob Hertzberger 52
Development of new technology Maturity Hans Dijkman 53
Effects of GigaPort NG Network innovation Research Pilots Market ICT-applications Innovation effects Effects on research Generic ICT-application services Network infrastructure GigaPort Next Generation  Network Project Effects telecommarket Applied innovation Primairy effects GigaPort Secundairy effects GigaPort 54
Effects on consumer IT:the industrialization of IT  Microsoft Data Center Chicago Google Data Center Eemshaven Ground floor: 56 containers One container:  1800 to 2500 servers >100.000 servers 55
Levels of IT services 56
f.e. 1423 Repositories worldwide holding over >20.9 Million items Repository66.org Repository Maps 57
…and an increasing number of Services… 58
… provided by suppliers in the cloud. 59
The Internet has become a nervous system connecting and augmenting our brains… Scientific & Educational methods can help  Knowledge Management to create opportunities to use and expand our knowledge. 60

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eScience, Education and Knowledge Management

  • 1. What Knowledge Managementcan learn fromeScience & Education Knowledge and the management of knowledge Dr. L.A. Plugge
  • 2. 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
  • 3. Topics SURF as facilitatorand innovator foreducationand research What is knowledge? What is Knowledge Management (not)? Academicknowledgestrategy How ICT changes research and education 3
  • 4. SURF SURF is the higher education and research partnership organization for network services and information and communication technology (ICT). SURF participants: 14 universities 45 universities for professional education 5 research institutions
  • 5. SURF – innovation & services 5
  • 6. 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 initiative www.surf.nl/wtr
  • 7.
  • 8. InnovationMethod (2) Life cycle phases 2 3 4 5 1 Technological scouting Services develop-ment Assessment studies Production Marketing Fasing out Technological development Client needs Inventory Client needs External Developments Plan for TA Business case Business plan Marketing plan Plan Fasing out service Plan termination service Feedback 8
  • 9. Areas of competitionandcollaboration Processes to outperform the competition Provide future Required competences Essential and uniqueto the organization type Common industry processes Edwards & Peppard Cranfield School of Management 9
  • 10. 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 10 10
  • 11. Topics SURF as facilitatorand innovator foreducationand research What is knowledge? What is Knowledge Management (not)? Academicknowledgestrategy How ICT changes research and education 11
  • 13.
  • 14. 14
  • 15.
  • 16. In other words: Knowledge is constructed and represented in our brain. The question is Can we represent knowledge outside our brain? Do documents containknowledge?
  • 18. Goal of knowledge representation Securing knowledge, outside humans Making it available to others Making knowledge less scarce Automate the creation of new knowledge 18
  • 20. Knowledge representation in rule based expert systems 20 Inference Engine User Interface Rules Facts
  • 21. Searle’s Chinese room Part 3 Part 4 21
  • 22. The Paris Hilton Problem
  • 23. IBM’s Watson The Match Day 1
  • 24. Some limitations ofknowledge systems Knowledge is represented in symbols Procedurele knowledge is represented in rules Conceptualknowledge is represented data “Brittleness” “Halting” problem “Grounding” problem How todefine the knowledge boundaries? 24
  • 25. Knowledge representation in Neural Networks 25
  • 26. Current ‘knowledge representation’ still lacks: (deep) Understanding Creativity Intuition Fascination Ingenuity / originality Creativity … 26
  • 27. Explicit and Implicit knowledge Explicit knowledge Can be coded Transferable Copyable Implicit knowledge Transferable, in principle… 27
  • 28. 28 depressive 14 2 13 7 agressive chaotic Implicit knowledge:Students versus Expertsdiagnosing patients depressive 6 0 3 3 8 9 7 agressive chaotic
  • 29. Explicit - Implicit Implicitknowledge is just as important as explicit knowledge Transfer of implicitknowledge takes time andphysicalpresence Examplesfromlearning: to drive a car toplay a music instrument howtoperform open heartsurgery Breadbaking machine… 29
  • 30. Topics SURF as facilitatorand innovator foreducationand research What is knowledge? What is Knowledge Management (not)? Academicknowledgestrategy How ICT changes research and education 30
  • 31. Knowledge managementis creating opportunitiesthrough strategies and practicesfor Knowledge Creationand Knowledge Transfer
  • 32. Nonaka’s & Takeuchi’s Theory on Knowledge Creation, 1995
  • 33. Knowledge exchange = Communication Sound Text Video Video & Sound
  • 34. What is the essence of 34 Lascaux (13 000 v. C.) Library of Congress
  • 35. Knowledge management process 35 Create Capture Organise Access Use Knowledge Creation Knowledge Application Knowledge Sharing
  • 36. Topics SURF as facilitatorand innovator foreducationand research What is knowledge? What is Knowledge Management (not)? Academicknowledgestrategy How ICT changes research and education 36
  • 37.
  • 38. Tony Hey, Stewart Tansley, and Krist in Tolle, The fourth paradigm, 2009
  • 40. Academic knowledge transfer (1) 40 revise Hypothesis Method Results Conclusions publisher submit judge produce publish Scientific world Reviewers Research group / Individual
  • 41. Lineair view of scholarlycommunication
  • 42. Tony Hey, Stewart Tansley, and Krist in Tolle, The fourth paradigm, 2009 Back to the e-Science Paradigm
  • 43. Topics SURF as facilitatorand innovator foreducationand research What is knowledge? What is Knowledge Management (not)? Academicknowledgestrategy How ICT changes research and education 43
  • 44. 44
  • 45. X-informatics & computational Xdata intensive science 25-50% of the experimental budgets are for SOFTWARE
  • 46. 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
  • 47. eScience is facilitated by merging technologies GT: grid technology OGSA: open grid services architecture WSDL: web service definition language WSDM: web services distribution management Bob Hertzberger 47
  • 48. Technology facilitates a knowledge driven research infrastructure 48
  • 51. Providing the opportunity to share and reuse Bob Hertzberger 51
  • 52. Sharing, using and contributing to infrastructure Bob Hertzberger 52
  • 53. Development of new technology Maturity Hans Dijkman 53
  • 54. Effects of GigaPort NG Network innovation Research Pilots Market ICT-applications Innovation effects Effects on research Generic ICT-application services Network infrastructure GigaPort Next Generation Network Project Effects telecommarket Applied innovation Primairy effects GigaPort Secundairy effects GigaPort 54
  • 55. Effects on consumer IT:the industrialization of IT  Microsoft Data Center Chicago Google Data Center Eemshaven Ground floor: 56 containers One container:  1800 to 2500 servers >100.000 servers 55
  • 56. Levels of IT services 56
  • 57. f.e. 1423 Repositories worldwide holding over >20.9 Million items Repository66.org Repository Maps 57
  • 58. …and an increasing number of Services… 58
  • 59. … provided by suppliers in the cloud. 59
  • 60. The Internet has become a nervous system connecting and augmenting our brains… Scientific & Educational methods can help Knowledge Management to create opportunities to use and expand our knowledge. 60