KM Labs : Knowledge Management Technologies

L'utilite de la representation des connaissances se situe dans l'Inférence.

Il existe plusieurs technologies dediees a la representation. Le Probleme etant leur pertinence par rapport au besoin.

Analyse des Outils :

- ontologies (philosophiques (etres) ; théoriques ou fixées par des règles (classification des univers physiques et abstraits ; techniques (savoirs, savoirs faires, procédures))
- thesauri (descripteurs (vocabulaires controles) + liens (taxonomiques (générique, specifique : hyponomie, hypernomie) ; méronimiques (composés); holonimiques (holons=parties indépendantes) ; synonimiques ; causalitifs (systèmes causants)
- cartes conceptuelles, cartes de K (mind mapping)
- graphes conceptuels (réseaux multipoints de vue, réseaux à facettes (points de vue fixes) : exemple application de couplage avec thésauri => thésaurus a facettes pour les vocabulaires stabilisés), exemple de facettes: système POPSI (Postulat Based Permuted Subject Index)
- structures qualia (roles)

Representation en logique
tautologies, regles, tables de verité, prédicats, modes, types (logique intensionelle), structures a traits ...

Enfin, on peut etendre le probleme de la representation des connaissances a la Culture en general...chers representants de la connaissance !

Here is an astonishing synthesis of tools for communication and information visualisation, all grouped in a Periodic Table. Elaborated by Ralph Lengler & Martin J. Eppler from the University of Lugano, Switzerland, they say "The organization principles should relates to the situation in which the visualization is used (when?), the type of content that is represented (what?) the expected visualization benefits (why?), and the actual visualization format used (how?) .




They have then " classified the visualization methods according to those challenges and requirements and came up with the following five dimensions.
• Complexity of Visualization: Low to High, referring to the number of rules applied for use and/or the number of interdependences of the elements to be visualized.
• Main Application or Content Area [how?, what?]: Data, Information, Concept, Metaphor, Strategy, Compound Knowledge. Furthermore members of this group can also be ranked according to their knowledge intensity, going from explicit, objective knowledge visualizations (like Data Visualization) to more tacit, subjective knowledge visualizations (like Compound Knowledge Visualization).
• Point of View [when?]: Detail (highlighting individual Items), Overview (big picture), Detail and Overview (both at the same time).
• Type of Thinking Aid [why?]: Convergent (reducing complexity) vs. Divergent (adding complexity).
• Type of Representation [what?]: Process (stepwise cyclical in time and/or continuous sequential), Structure (i.e., hierarchy or causal networks) "
(Via Outils Froids)

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