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I like to think about knowledge as coming in two types:

First, there is knowledge like physics, math and the like, which is about the inner workings of things. As such, it easily tends to become abstract and difficult, but in terms of volume, you need only a little to be able to do a lot.

Second, there's knowledge that's really specific: The name of a place, the date of an event, how many stars are in the night sky. The answers are mostly rather easy to congest, but there's an almost unlimited volume of them, and each on its own has little worth.

What is the best way to describe these two types of knowledge?
For example, deductive knowledge would probably fit well for #1, but it's opposite 'inductive' doesn't really fit #2.

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  • Contrasting mathematical truths to facts about the world, you could make the distinction between necessary and contingent facts. However I don't think this quite fits because there are mathematical "trivia" facts (e.g. 55 is the largest fibonacci number that is also a triangular number) that fit more in the second category, despite being necessary truths.
    – samgak
    Sep 14, 2018 at 4:03
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    You might find this page on Wikipedia interesting, which describes the theory of fluid and crystallized intelligence. With that as a basis, I could suggest fluid knowledge and static knowledge (crystallized is a bit fancy for my liking!)
    – MotherBrain
    Sep 14, 2018 at 10:32
  • @MotherBrain A good suggestion! Fluid knowledge would, as a transfer, fit very well, both metaphorically and from the definition. Static is a little more rough as metaphor, but still all in all a good fit
    – Sudix
    Sep 14, 2018 at 11:53
  • @samgak Modal logic is quite complex, and I have only a vague understanding of it, so I'm a little uncomfortable using this terminology. For example, any deduction in math has (quite a few) hypotheses. If you take them away, doesn't the result turn into a contigent fact?
    – Sudix
    Sep 14, 2018 at 12:42

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These are usually cast as procedural and declarative knowledge. The first is rules and how to apply (process) them. The second is observed data. (The rules are deduced from patterns in the observed data).

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  • Reading from the definition, this is an exact fit. It's a pity the terminology is being overused to the point where its actual meaning is starting to fade away
    – Sudix
    Sep 15, 2018 at 5:19

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