The “data/information/knowledge/wisdom” (DIKW) model identifies four levels of learning and how they build on one another. In the past I’ve found it difficult to separate the definitions between these four levels, but now I have working definitions that I feel comfortable with and I’d like to share.
Data means raw data, like the temperature in a room right now. Instruments measure data.
Information summarizes data, e.g. a trend line of temperature in a room over time. Data on a graph is information. An equation to summarize how data has behaved over time would be information.
So far so good, I hope. Data and information are the easy ones.
Knowledge is a predictive ability for the future. A trend line of how data has behaved in the past is not necessarily knowledge.
The example I normally use is with birthdays. If four (4) of my friends had a birthday on Monday, and three (3) of my friends had birthdays on Tuesday, and two (2) of my friends had birthdays on Wednesday, how many of my friends (?) will have a birthday on Thursday? If you don’t know anything about birthdays, you’d say one: the pattern looks like 4, 3, 2, 1. The knowledge, in this case, is that birthdays recur annually.
Knowing that birthdays recur annually gives you a predictive ability for the future. A process under statistical control also provides a predictive ability for the future.
In the case of temperature, knowing there are four seasons and the temperature patterns for your part of the world helps you know whether the room will tend to be warmer or colder.
I’m still working on my definition of wisdom, but “hard-won” is definitely part of the definition. I’m leaning towards saying that wisdom can be summarized in a sentence or two.
Wisdom is the distillation of pain and experience that allows you to describe eloquently a lesson for others. I worked on an ITSM tool implementation for 18 months and came up with about eight sentences of “ITSM tool wisdom.” Each statement was extremely valuable, however, e.g. “any vendor patch introduces new features as well as bug fixes.”
In the case of room temperature, wisdom might be, “people tend to go to sleep after lunch if the temperature exceeds 72°F.”