Creating meaningful K-map taxonomies
by Volker Weber
Among knowledge management professionals, a fine-tuned, easy to understand taxonomy is just about the most beautiful thing in the world. After all, here is a visual representation of that most elusive yet critical concept, what your organization actually knows. With a well-constructed, meaningful taxonomy, users can quickly find the right people and information they need to achieve their goals. It's equivalent to having instant expertise at your fingertips, ready to answer questions you may have at any time. Sounds wonderful, doesn't it?
Of course, in the real world, it's historically been very difficult to construct a useful taxonomy of corporate information, especially in larger organizations. Indeed, before the advent of computers, it was all but impossible, particularly for major companies where employees came and went and new technical documents were constantly added to the corporate store of knowledge. So in most situations, taxonomies tended to either be superficial and general, or constantly out of date -- often both.
Lotus Discovery Server helps change all that. Now you have a state-of-the-art tool that can keep track of your documents as well as your user's skills, regularly checking for updates and additions. More importantly, Discovery Server uses complex mathematical metrics to analyze the content of your your documents and the experience of your employees, find affinities between them, and place them into categories. These categories comprise a computer-generated taxonomy, or in terms of Discovery Server vocabulary, a K-map.
But no computer program, however sophisticated, can precisely predict exactly how a particular organization may want to structure its content. So to build a truly meaningful, easy to use K-map taxonomy, humans and computers must work together. This requires some time, patience, and creative thinking (on the part of the humans anyway). But if done correctly, the results are more than worth it.
This article offers advice on building useful, robust K-map taxonomies. It presents things to consider when deciding which type of taxonomy scheme works best for your organization and who should be involved in the process. We'll prepare you for all the major steps involved in planning and creating a taxonomy.
