Knowledge constitutes an additional level of meaning that we derive from information through some process. Sometimes this process is observational. What happens when it gets cold? Sometimes it is computational where data are processed to arrive at the higher level of meaning that represents knowledge. Data when interpreted within a certain context yields information having meaning. Information when applied within a certain context yields knowledge. A more important component in the concept of knowledge is that it also represents how we apply the information contained within it.
EX. WM-4:
Meanings of data have impacts on how an organization runs. This is an extension of information to knowledge. People who manage aircraft, for example, will be concerned with the impact of cold weather on its fleet. Observational knowledge of the cold told engineers long ago that ice can build up on an airplane reducing aerodynamic lift and potentially impeding the performance of its control surfaces. In extreme cases, this can have disastrous consequences. Here we see that how we manage data can sometimes have life-critical implications.
Thus, we are compelled to transform this type of knowledge into a computational context as the following set of rules extended from our last example.
IF temperature <= 0 ° C THEN cold = true;IF cold == true THEN notify ground crew to de-ice aircraft.
By this point in the text it is clear that representing reality – facts, information, and knowledge – can be tricky. This is the topic of the next section.
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