Reply to LO20305
Dear LO'ers,
Knowledge Management (KM) is a very interesting topic. I would like to
share with you an idea which I had already for a couple of years. It has
to do with my work in the library of a university: how to manage
information?
I realise that information management is something less complicated than
KM, but both have some common features. The most important is: what is the
way to organize knowledge, store it and label it with subjects or
keywords. Are we able to construct a database with knowledge, which is
accessable for the fellow knowledge workers?
Let's see how an ordinary catalogue-card of a library is composed. It
usually contain the hard facts: titel of book, name of author(s),
publication year, publisher. Than the 'soft' facts: shelf number, keywords
and possibly a classification code. Keywords and classification (a code
referring to a specific (sub)discipline of the subject) are the most
sensitive of all features on this catalogue card for subjectivity. And the
indexer's thoughts must match with those of the clients of the catalogue.
Now, nearly all library catalogues have been computerised, some extra
possibilities are available, using the same data: combining these data by
boolean operators (AND, OR, NOT).
It is a pitty, that the electronic catalogue record, hardly differs from
the old fashioned catalogue card. No use has been made of the extra
possibilities which this medium has in it: graphics and colours. We are
all familiar now with small pictograms at the buttons of our software
programs, we are used to different character sizes, underscores, bold,
italics, underlining, etc. And in some software it is easy to use even
coloured characters and words.
Cartographers have used these possibilities very intelligently. I will ask
you to study the general legend which is used for the maps in a
schoolatlas. You will probably see:
line elements for: boundaries of countries, different kinds of roads
(highways-secondary, tertiary roads), rivers, railroads, etc. Distinction
is made by use of different colours and different typography
(double/single lines, dotted or dashed or straight, etc.)
coloures for: water, land, cities
shades for: elevation differences in depth of waters and altitudes of
mountains
typography in geographical names for: waters, cities, countries, regions
and counties (with the use of italics, capitals, etc.)
Sometimes names of cities even are differentiated to indicate range of
number of inhabitants, whether it is a capital.
So you see that with the combined use of typographical and colour
differences a wealth of extra information (combined) is included. And all
these things are very clear to recognise.
In my mind these types of techniques are very usable for 'describing'
knowledge. With the use of , say 5 different colours, characters in
normal, capitals, italics, bold and underlined, and 3 different sizes of
characters, one is able to distinguish 75 different weights, meanings,
uses, etc. of a keyword or index. This gives a much richer picture of a
label.
So how do we label knowledge? knowledge that should be traceable in a
database. Maybe we should make use of small sentences (syntaxis) composed
of words (semantics).
I have a proposal. In a company where a knowledge database is constructed,
every employee has the possibility to describe his knowledge in a number
of sentences ('one-liners'). This could be possible in 25 - 100 sentences,
but the number does not matter, it is to get a feeling of the size.
Each of these sentences should be at least composed of a subject, a verb
and an object. For instance: LEO MINNIGH STUDIES REMOTE SENSING.
Further information could be included in the same sentence, like
adjectives.
The final result of such sentence will be a crisp description, where the
relation of object and subject is best described. This means that also the
method in use, time-span, place, or area, etc. should be included.
Such sentences include present and past knowledge, hobby, sport, travel
experiences, education, lectures, conferences, etc.
All the semantical elements in the database are searchable. The graphical
characteristics of words retrieved, will indicate the syntaxis. So we have
a good method to distinguish 'REMOTE SENSING' as subject, or as object, or
as verb or method. Once a query has resulted in some hits, the complete
sentences will appear. But before we look at these sentences, we have much
more tools available to filter and fine tune the first results. Much more
than only the boolean operators, because we could use the graphical
characteristics for further filtering.
This idea could be enriched with the use of pictograms and other features.
The succes of such a knowledge database depends largely on the openness of
the employees. They must describe their knowledge and they must be open
for sharing it with others.
I am eager to hear other ideas of knowledge description. And I am curious
if readers have experiences with KM in practice.
dr. Leo D. Minnigh
minnigh@library.tudelft.nl
Library Technical University Delft
PO BOX 98, 2600 MG Delft, The Netherlands
Tel.: 31 15 2782226
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Let your thoughts meander towards a sea of ideas.
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--Leo Minnigh <L.D.Minnigh@library.tudelft.nl>
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