When you manage information and there is entity disambiguation meaning that one thing could have multiple terms but still retain meaning computing systems are not capable of doing this with ease as opposed to what people do in terms of rationalizing the the dynamic an entity. If we are looking to define knowledge outside of business purpose it can become just as complicated to manage as node or entity with multiple tags.
http://sivers.org/ff Watch that first… “The first follower transforms a lone nut into a leader.”
What is KM? Without all the epistemology and math..
Primer #1: Join the party!
1. We live in a knowledge-driven economy and society (Yelden, 2004) and we have to get the right information to the right people at the right time!
2. 99% of work people do is knowledge-based (Wah) therefore its management (KM) drives the bottom line*
3. It’s estimated that 90% of an organization’s knowledge is in people’s heads (Beazley et al, 2002) and that’s got to be captured/recorded
4. Lost knowledge = lost opportunities**
5. Good news: we’re already doing KM in all our activities (it’s a cross-cutting issue), but we can do it better
6. KM lets staff USE their knowledge and helps produce synergies among teams and projects, which helps build a sustainable technical and programmatic knowledge base
1. Organizations are looking to monetize “working together”
2. Knowledge transfer is sloppy and is a problem.
3. People in general are stubborn and want to do things “their way”
4. KM is buzz. (that is a good thing)
5. Knowledge Management is different from information management because it deals with context and comprehension. (Cohen)
6. Six bullets is one bullet too many.(Cohen)
Still a lot of discussions on this subject and it can become very complicated as you know. Fundamentally when we are talking about knowledge in KM we are talking about it in context of use for business purposes.
Knowledge is not defined in an accepted standard. Knowledge itself is up for grabs as you know which is why there is epsitemology (dangerous to go there).
What we look to address is the two types of knowledge that we can identify as part of a “capability to create, maintain, enhance and share intellectual capital across the organization in support of business or sector objectives.”
The two types are
Tacit– which is believed to be personal in nature and difficult to extract.
Explicit-which can be articulated and codified. Explicit knowledge can be easily disseminated through technology, while Tacit knowledge must be drawn out of people under the right circumstances at the right time.
In other words, the people who are discussing knowledge management look to simplify knowledge down to these two fundamental areas of knowledge types. There really is no “right” answer. What this body of work looks to identify and achieve is the idea that information or data itself has less value disassociated to context and intent. It has great value when use “for purpose” mostly business but of course we can see value in other areas.
Does Watson have knowledge? (IBM Watson if you are asking)
In that case if a machine understands data because it has a schema or pattern that it recognizes, it may (the machine) further know what to do with this data after sifting through a series of complex algorithms and of patterns programmed. It still leaves out the tacit portion at least that is what I think.
This KM field is the same as every other, there is a hook, repetition and then the song is over. The reason why I find value in this area is because it is bringing to light a gap in dealing with people management outside of human resources. I am not just addressing Myers Briggs either, I am talking about the basic things that we seem to have forgotten. Like be nice to people. Treat people the way you want to be treated. Communicate.. collaborate… cooperate.. etc. Identify purpose and value in those around you. Create small agile teams.. etc. My point is that knowledge management can’t avoid people who most of the other areas of work we deal with can. In KM technologies are identified as enablers not drivers.
All of the areas of work that I have researched and practice lead to the same conclusion, we ignore and take for granted the very reason that we are doing what we do. If we don’t practice reminding ourselves of our purpose or find purpose in our work, we devalue everything we attempt to take on by creating technologies. Example.. text and im.. we do this instead of pick up the phone or walk over in person to see a person. We miss 80% of the conversation…
David Skyrme does a good job laying out some field basics (http://www.skyrme.com/resource/kmbasics.htm)