Updated: 6/23/2005; 9:36:57 PM.

Mathemagenic


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  Thursday, July 03, 2003


  I-KNOW: Track 2 "KM in industry"

Marianne Kukko from Finland presents the results of interviews with HR practitioners from 44 Finnish companies. For me the results are biased towards HR activities (e.g. training). The interesting detail of the study is about language: lack of Finnish KM terminology makes things more difficult.

Ulrich Kagrlmann talks about SENEKA project. Between other things he talks about KM trends:

  • globalisation
  • regionalisation
  • dynamisation of job profiles
  • continuous training on the job
  • integration of job and private life
  • multiple job
  • micro-companies

Matteo Bonifacio speaks again: this time the richness of diversity in knowledge creation and about a contradiction between social and distributed way of creating knowledge and centralised technology support for it diversity. He examines several theories that say the same: diversity is good for innovation.

Then he talks about technology adoption, that happens in three ways: technology fits people's practice, technology is shaped and changed by these practices or practices are changed to adapt to technology. Practices are social and distributes, so centralised technologies usually fail. If centralised technology succeeds it may be worse: it will imply the reduction of diversity and, as a side effect, of innovation and adaptability. So, next logical step would be to let people have their local technologies, but provide ways to coordinate between them (this is my simplification of distributed KM approach).

One of the question from the audience was about number of technologies that one can cope. I share this concern given the number of communication/discussion tools I use. I have some follow-up thinking, but it's not getting out of me now :)

More on: I-KNOW 

  I-KNOW: comments on posting

Yesterday I didn't make many notes: it's not easy with technical demos, presentations were quite short and I stayed too far from the plug, so could not be on all the time. Today it's easier: keynotes were almost one hour long, presenters have more time too and I'm smarter to come early to find plugs :)

Please forgive not clean code and editing after posting. I'm typing in Word (because it check spelling and I make a lot of mistakes with blind typing) and posting it in the breaks (as I don't have wifi card and have to login from a special room).

More on: I-KNOW 

  I-KNOW: Jay Cross

Jay Cross gives funny and entertaining speech "The rise and fall and rise of eLearning" (slides should be on-line, but it seems Jay needs more time to make it happen). He talks not only about e-learning, but also about "hunting elephants", learning as network building, blogs and enterprise software. He asked how many people in the audience were reading and writing blogs: around 10 and 2 respectively :)

I'm getting more and more interested why blogs are not used much in research. I wonder if I can make a paper on it (as KMSS paper deadline was extended till 25 July, I hope that I can push myself to write it till then).

More on: I-KNOW 

  I-KNOW: Peter Schutt

Peter Schutt from IBM speaks about "post-Nonaka knowledge management". He discusses scientific management based on Taylor's approach to people, proposes that current business theories (e.g. TQM, BPR) are building upon Taylor too and then suggests that we are at the turning point now, because scientific management can not be applied to knowledge work.

He states that KM is not about managing knowledge. It's about managing knowledge work and about productivity of knowledge workers. (This reminds me things that Jim McGee is writing all the time).

He talks about stages in KM history and gives a couple of great citations:

since knowledge is intangible, boundaries, and dynamic and cannot be stocked it has to be exploited where and when it is needed to create values (Nonaka, 2001, "The emergence of "Ba")

You cannot manage knowledge like you cannot manage love, patriotism or your children. But you can set up and environment where knowledge evolves (Larry Prusak)

The rest of the presentation is focused on three things that are important if you would like to create an environment to support knowledge workers: organisation&culture, processes, information technology. The slides contain interesting frameworks to think about, but too complex to write in a blog. Just a couple of notes:

Organisational knowledge is 4% structured, 16% unstructured and 80% experiences and expertise of people, but 80% of IT budget spent on managing that 4% (refers to analysts from somewhere)

Use of baseball and soccer metaphors to compare old style culture and KM supportive culture.

See also The post-Nonaka Knowledge Management article by Peter Schütt

More on: I-KNOW 

  I-KNOW: Ben Shneiderman

Ben Shneiderman speaks about Leonardo's laptop (which is his new book). I guess main ideas should be somethere on-line, so I'll search for them rather than writing them here.

Things I found interesting:

More on: I-KNOW 

  I-KNOW: Ontologies +

I was surprised that a lot of things for the rest of the day were quite technical: social issues "around communities" and then jump to presenting systems to support them. I'll dig out the links to demos and sites and post them later.

My taking from this session is about choices to make during ontology building process and some implications (I'd like to make a mind map out of it, but don't have any software here, but at least it's something)

  • one expert vs. group involved
  • expressiveness (detailed and complex ontology) vs. maintainability (simple ontology)
  • automatic vs. manual
    • automatic: quality is questionable
      • when ontology is good? mainly depends on user tasks (also: ontology in corporate settings usually reflect power distribution)
      • tools to use and their costs?
      • change: too fast if generated on the fly
    • manual
      • costs: people (+learning curve to learn about ontologies), time, iterations
      • process can be as valuable as ontology itself: commitment + questioning mental models and reflection
    • evaluation instruments: ontoclean, usage mining
  • group vs. organisational ontology
    • depends on company's type/size/culture (diversity)
    • how to combine/relate group ontologies into organisational ontology -> ontology mapping
      • multiple ontology mappings are not easy (usually some common structure for all ontologies is needed) 
      • monodirectional mapping (objects from a certain system, e.g. database, are mapped into an ontology, so it can be used to retrieved them
  • other issues
    • lessons learnt from db modelling
    • unstructured data is difficult to extract/create an ontologies
    • ontology ownership

Note: You may be surprised why I'm talking about ontologies. At work I'm involved in a process of ontology-building, so I have a lot of practical questions to be answered. My interests are not so much about technical details, but more in social and organisational issues around it. Where do you start in order to build an ontology? Whom do you involve? What roles to they take? What tools can help? Will be an ontology accepted by others? How do you update and maintain an ontology? Any references that answer these questions are welcome

More on: I-KNOW ontologies 

  I-KNOW: time for learning

This is a bit polished version of my notes from the I-KNOW 03 day 1. I went to the workshop about communities.

Oliver Vopel: "In order to reduce complexity and ambiguity one does not need more knowledge but more confidence"

Matteo Bonifacio is a great presenter I'm happy that he will be speaking at KM summer school. He presents two different scenarios about a same person. One with decision-making as a result of access to all kind or resources in KM system and another on changing a reality by asking questions (so your prediction at the end is not a prediction, you made it). Then he refers to four groups of KM approaches to explain and contrast these scenarios. There is more in the presentation, so I hope it will be on-line.

There is an interesting comment that makes a dichotomy between time to learn vs. time to do things. Matteo adds that probably it's not about time as such, but about responsibility that you have for the results. If it's high you will focus more on getting things done and have less space for learning. With less responsibility to learn more, but sometimes do not get results right. Jay Cross adds that learning is part of the work. Another comment is related to the time horizon of learning: learning for the future looks like learning, but learning for immediate work looks like work.

I'm thinking about both perspectives: each of them is true. I agree that any work you do brings you something to learn, so learning is embedded into work. But I think that this is mainly "experience building" part of Kolb's learning cycle, with some degree of reflection. But you need more time and less work pressure for more reflective mode of learning and definitely for discovering and changing your mental models and learning habits (see a bit about it in my discussion with Sebastian)


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© Copyright 2002-2005 Lilia Efimova.

This weblog is my learning diary. Sometimes I write about things related to my work, but the views expressed here are personal and do not necessarily reflect the views of my employer.

 
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