enter image description here

For my philosophy discussion group, I am looking for real life examples that would fit the above illustration. What would be some good examples?

Data is a collection of facts, while information puts those facts into context. While data is raw and unorganized, information is organized. Data points are individual and sometimes unrelated. Information maps out that data to provide a big-picture view of how it all fits together. Data, on its own, is meaningless. When it’s analyzed and interpreted, it becomes meaningful information. Data does not depend on information; however, information depends on data.

P.F. Drucker: information is "data that has been converted into a meaningful and useful context for specific end users"

Information offers rises to the concept of facts and data; knowledge is the understanding of the matter or subject. Information is a combination of context and data; is a combination of experience, perception and information.

Efraim Turban, Ephraim McLean, James C Wetherbe: data is elementary descriptions of things, events, activities, and transactions that are recorded, classified, and stored but not organized to convey any specific meaning; information is data that have been organized so that they deliver meaning and value to the recipient; knowledge consists of data or information that have been organized and processed to convey understanding, experience, accumulated learning, and expertise as they apply to current problem or activity.)

No philosopher, it seems, rejects any of the five categories above. But do most philosophers broadly recognize a gradation of categories from data to wisdom? Are there examples that help to clarify the relationship between these categories?

  • Could you please add short verbal definitions of the five concepts of your diagrams. The definitions should define the scope of each concept and establish a border between different concepts. I consider your question interesting and well-suited to this forum. Thanks.
    – Jo Wehler
    Commented May 20, 2022 at 9:31
  • 1
    This strikes me as more of an analytical puzzle than philosophy. "We've got all these related words with mostly fuzzy and interleaved meanings; let's come up with distinctions between them and form a sequence". Philosophy goes the other direction. Instead of starting with the words and looking for distinctions, you start with a distinction that you are exploring and you try to come up with words to differentiate the concepts. Commented May 20, 2022 at 10:29
  • 1
    @David Gudeman Don't you agree that the OP's 5 terms are not the beginning but the condensation of vaguely guessed distinctions? Philosophical questions, answers and discussions can only profit from clear definitions and demarcations. Why not illustrating the result by diagrams?
    – Jo Wehler
    Commented May 20, 2022 at 10:38
  • 1
    Silly example: Data: some "raw" temperature measurements. Information: time and place of the measurements. Knowledge: temperatures measured compared to seasonal averages and historical trends with prediction for short-middle term evolution. Insight: hypotheses about long-term climate evolution. Wisdom: no wisdom "available" to human beings. Commented May 20, 2022 at 10:47
  • 1
    Where do question-answer considerations fit in? Do questions come before data? But what about the information/knowledge/etc. we need to ask questions in the first place? Or what about new questions occasioned by further information and operations thereon? Commented May 20, 2022 at 15:27

2 Answers 2


Short Answer

Philosophers certainly use these categories frequently in their discourse, and in fact, in one metaphilosophical theory, wisdom is the primary goal of philosophy, sometimes called "philosophy with the big P". I suspect most professional philosophers would agree with the claim that wisdom is either a necessary or sufficient condition for eudaimonia. But there are no standard set of philosophical precising definitions that define each. Definitions from the OED is as likely as you'll get to some sort of standardization of these words.

Long Answer

It is arguable that the basic unit of philosophical discourse is the proposition. At least in the analytical tradition, heavy emphasis is placed on truth-conditional semantics, and much ink is spilled over proving or denying the veracity of claims. There is God. There isn't God. Numbers are real. Numbers aren't real. We are more than our bodies. We are not more than our bodies. And the mind controls the body. The mind doesn't control the body. But in that process of discourse and truth evaluation, different philosophers make different sorts of claims. Enter the epistemologists and their passion for epistemic justification. There are beliefs, and then there are beliefs!

What was once just "some stuff people say" is now at a minimum recognized as belief, knowledge, and wisdom. Most philosophers dead or alive recognize these three categories as much as they may struggle over drawing boundaries. Both information and insights are words that hold some additional nuances of connotation. Of course, any epistemologist worth his salt is going to have a position on these five terms, and be capable of dueling with words to affirm their own knowledge (or mere belief depending on your personal views). Let's take a look at some uncontroversial statements about each.

Data vs. Information

Perhaps one of the simplest acts necessary for creating a taxonomy of knowledge is the act of dichotimization. Leibniz's Law comes to mind in such an act. It would uncontroversial among thinkers, I'd argue, that the data-information dichotomy is utilitarian practice when working with large swaths of representations (SEP), the philosophical term that might be used to subsume all of the categories you mention. In my own day to day existence, when I deal with data sets which might exceed millions of records with a hundred plus fields, it is useful to distinguish between raw data, sets of values mapped to a variable with sets of variables mapped to a table, and information. For instance, in an ICD code set, there are more encodings than, I suspect, most doctors are aware of. But, can I take those sorts of codes within the context of a task and do something practical and meaningful for them? Can I translate them into an EDIFACT data structure to send them to a hospital overseas? Hence, the raw material is a collection of codes, and the product is perhaps an insurance claim that a hospital in Norway might be able to use? Data and information.

Data, Belief, and Knowledge

Data and knowledge is an entirely different distinction. Any child might point to a computer, utter 'computer' and say, "I can read those words" of some text. But can a child understand the purpose of a set of healthcare records? Can they take those records in the spirit of big data and mine them for analytical conclusions? Of course not. It's questionable on some days if I can. Enter Ryle's distinctions of knowledge-how and knowledge-that. And this use of knowledge is different from the belief-knowledge distinction, which is arguably a more important distinction which begins to turn on the idea of justified, true belief. I may believe that a population of clients has a predisposition to cancer, but can I prove the claim? My knowledge of the veracity of a claim, therefore is paramount if I'm making practical, real-world choices. Vladimir Putin believed he could take Kyiv in 3 days, but did he know? In retrospect, obviously not!

Insights and Intuition

MW defines insight as:

1 : the power or act of seeing into a situation : penetration
2 : the act or result of apprehending the inner nature of things or of seeing intuitively

Talk about 'open to interpretation'! The 'inner nature of things'?!? 'Seeing into a situation'? Here is a recognition that not all propositions are created equal. The lay definition of an insight reflects the concepts that there is a deep, inner nature. I've always taken this to mean that intuitively philosophers are very much concerned with distinguishing the essential from the accidental (SEP), the necessary and sufficient, or perhaps distinguishing from among coincidence, correlation, and causation. All of these conceptual distinctions are important, because despite the protestations of the over-confident, human reason is highly normative and defeasible.


This is often touted as the best end to philosophy. While professional tribes of Continental and analytical philosophers often have very technical pursuits and rigorous conditions, taking philosophy back to Socrates, we can see there might be a higher purpose be it eudaimonia or Truth or salvation or satori or whatever you want to call it. In this vein, wisdom is about the teleological. Does life have meaning? How should I make decisions? What's the best way to do anything? Wisdom is often understood as a gradation of knowledge that has a normative aspect. Anyone can beat a dog into submission, but perhaps by whispering in his ear, one avoids getting bitten in the future. Albert Camus and his absurdism is a great example of contemporary philosophy that isn't technical at all. In fact, Camus espoused beliefs about rebelling against all of the language of philosophy and embracing a passionate, well-lived, personally meaningful life in the face of a naturalistic explanation of the universe. We see in Camus a sort of anti-philosophy.


Philosophy means many things to many people. Metaphysics has always been the art of selecting among "first-principles" and then interpreting the world. Having a consistent, meaningful, and useful taxonomy of propositions is one of the necessities of having a philosophically durable worldview. As we take basic units of meaning (morphemes, perhaps?) and build propositions, arguments, and theories from them, it helps to see how meaning itself can be identified with other practices, such as epistemic justification or teleological planning.


Motivated by Mauro’s links and his example I propose the following working hypothesis concerning the „Big Five“:

  • Data: Observed phenomena recorded.
  • Information: Recorded data classified and structured according to suitable criteria.
  • Knowledge: Successful test of a theoretical framework explaining the obtained data clusters.
  • Insight: Confirmed general hypothesis also for similar cases about the mechanism behind the phenomena.
  • Wisdom: If necessary, establishing practical consequences.

Improvements welcome :-)

  • Please make any improvements as comment or separate answer, but not into my original answer. Thanks.
    – Jo Wehler
    Commented May 20, 2022 at 19:23
  • My bad! Will mind that stipulation in the future.
    – J D
    Commented May 20, 2022 at 20:12

You must log in to answer this question.

Not the answer you're looking for? Browse other questions tagged .