Knowledge: Definition, Types, Usefulness

The Knowledge Pyramid: Data, Information, Knowledge, and Wisdom (DIKW)

(From https://en.wikipedia.org/wiki/DIKW_pyramid)

The Knowledge Pyramid represents a model, actually any models, of possible structural and functional relationships between a set of components, usually four: data, information, knowledge, and wisdom.

The point is that information gets gradually refined from raw data, through actionable knowledge, to some general or strategic knowledge (wisdom).

Earlier versions of the Knowledge Pyramid excluded data (how do we tell between data and information?), while later ones excluded or downplayed wisdom (possibly as something too vague or spiritual). Still other versions include additional components. Also, this model is not always presented as a pyramid but as a chart, a chain or flow diagram, sometimes even as a continuum.

In 1987, Czechoslovakia-born Milan Zeleny mapped the components of the hierarchy to knowledge forms:

  1. data matches know-nothing
    2. ,
  2. information matches know-what
    3. ,
  3. knowledge matches know-how,
    4. and
  4. wisdom matches know-why.

Let's try to provide an example of the distinction between data, information, and knowledge...

Data versus Knowledge

In the context of DIKW-type models, data is conceived, according to Zins' 2007 formulation, as being composed of symbols or signs, representing stimuli or signals, which, in Rowley's words (as of 2007), are of no use until ... in a usable (that is, relevant) form, that is until they become information.

Data is as yet uninterpreted, meaningless in itself, whereas information consists of interpreted data (or the interpretation of data).