Three core features of these models:
- Data, information, and knowledge are distinct concepts (as opposed to synonyms).
- Information is higher-level than data. Knowledge is higher-level than information.
- There is at least one more level above knowledge.
Data vs. Information
There is a lot of emphasis on the etymology of "data" as something which is "given"; it's there from the start and needs to be processed, refined, selected, vetted, etc. in order to produce information. A common analogy is the refining of pure metals (information) from ore (data). Sure, someone had to mine the ore or collect the data, but it's only useful as raw material for the process of creating information.
Problems with Data vs. Information
"Data" and "information" are both common words in non-technical English which don't convey the kind of sharp contrast used in DIKW models. We can already talk about "raw data" as opposed to "processed data" or "organized data." There's nothing odd about using "personal information" to refer to a Social Security Number, though this would fall under the data category in many DIKW models.
Considering (1) these are fairly close synonyms in non-technical English, and (2) the important distinction captured by DIKW's contrast of data vs. information can be conveyed by a variety of evocative phrases like "raw data" vs. "processed data," I argue that re-using these words in a technical sense muddies up communication without a good reason.
Plus, one person's given data is another's processed data. For example, the global average temperature in 1845 may look like a simple point of data to someone collecting such numbers for use in climate research. But that number has a complex origin story involving instrument calibration, tree ring measurements, statistical analysis, etc. There isn't a natural distinction between input stuff and output stuff when data/information is so often processed in an iterative or recursive way.
Information vs. Knowledge
According to different versions of DIKW, knowledge concerns the application of information, or "know-how" as opposed to "know-what," or expertise that exists within a human being, or an understanding of how different kinds of information relate. I'm seeing all sorts of ideas here, usually (but not always) about the transition from inert facts to taking action.
A Problem with Information vs. Knowledge
In non-technical English and in mainstream philosophy of knowledge, we do understand that what we know — or at least what we believe — has a profound effect on the way we take action, but also that knowledge is more-or-less inert before adding motivation or goals. "The application of knowledge" is synonymous with "the application of information."
The most charitable way I can see knowledge working as a "next step" to information is to focus on the implication that knowledge is internal to a decision-maker. The word "information" seems to more easily allow disembodiment; but then again, we don't think it strange to point at shelves of books and talk about "all that knowledge."
Overlapping Meanings, Not Hierarchy
You may have figured out by now that I'm not a fan of the DIKW hierarchy. I believe its success is due to the way it suggests new value or new information can be added to existing data/information/knowledge by doing some work with it. Information professionals would, of course, want to promote this general idea. It is an important idea!
However, the DIKW hierarchy doesn't seem to reflect either the common usage of its terms or how the world works. Nor are the technical uses of its terms well-defined enough to let professionals in these fields communicate precise concepts without further clarification. Its vices outweigh its virtues as a conceptual model.
If someone could come up with a catchy way (besides a pyramid chart) to convey the key idea about adding value through working with information, I think we could manage to do away with DIKW.
1. Rowley, J. (2007). The wisdom hierarchy: representations of the DIKW hierarchy. Journal of Information Science, 33(2), 163-80.