Information and knowledge management, both in theory and practice, often refer to so called DIKW pyramid model representing data, information, knowledge, and wisdom (Figure 1). However, there is very little agreement about the model and many of its aspects. No one can certainly determine when was the pyramid representation used for the first time, or who was its creator. There is also very little agreement about the meaning of the hierarchy, definitions of its specific layers, and even less “in the description of the processes that transform elements lower in the hierarchy into those above them”1.

Figure 1: DIKW model

The pyramid starts with data and builds upon it in each follow-up step. Data is the product of observations or measurements, and is usually of no value until processed and turned into information by placing it in a meaningful context. “Data is a set of discrete, objective facts about events… Data describes only a part of what happened; it provides no judgment or interpretation and no sustainable basis of action… Data says nothing about its own importance or relevance.”2 However, it becomes information as soon as it is given some meaning.

A number, a symbol, a character or a word is meaningless unless placed in some context. It is the context which gives data some meaning, and thus make it informative. Information is created through study, investigation, aggregation, critical thinking, and by putting data in some relation or connection. Minimalists believe that data is represented through symbols, so is the information, but in more complex forms such as words, sentences, statements, statistics, diagrams, charts or similar.

Knowledge is placed at a next level of the DIKW pyramid. It involves ability to understand and to make use of available data and information to make decision, solve problems, offer solutions, and so on. Human cognition is required to transform information into knowledge by adding value. In other words, information becomes knowledge through cognitive effort. As a result, and unlike data and information, knowledge is very personal, contains judgment, and involves individual values and beliefs.

Some authors believe that wisdom is very difficult goal and hardly achievable. Wisdom is related to our acquisition and use of knowledge in a wise and responsible manner. It is the application of intelligence and our previous experience toward the attainment of a common good. Wisdom is the highest level of abstraction, with vision foresight and the ability to see beyond the horizon.3

The DIKW model sees data as a prerequisite, a building block, of information, information as a prerequisite for knowledge, and consequently knowledge as a prerequisite for wisdom. Some researchers disagree with that view and argue that the pyramid should be turned up-side-down. In other words, through a process of de-contextualization of knowledge, or reversed processing, information and data emerge. As a prerequisite, we need to have already built knowledge structure and information framework to comprehend available data. Data is created from information by putting information into a pre-defined data structure that completely defines its meaning.4

Traditional hierarchy of data, information, knowledge, and wisdom needs to be carefully reconsidered, particularly in the era of artificial intelligence, digital transformation, and modern information and knowledge management.

Information consists of data, but data is not necessarily information. Wisdom requires knowledge, but knowledge is not necessarily wisdom. Accumulated data is not information. Accumulated information is not necessarily knowledge, just like accumulated knowledge is not wisdom.

References

  1. Rowley, Jennifer (2007). “The wisdom hierarchy: representations of the DIKW hierarchy”. Journal of Information and Communication Science. 33 (2): 163–180. doi:10.1177/0165551506070706.
  2. Davenport, T.H. (1997). Information Ecology: Mastering the Information and Knowledge Environment Oxford University Press, New York
  3. Awad, E. M. & Ghaziri, H. M. 2004. Knowledge Management, Upper Saddle River, NJ, Pearson Education International.
  4. Godbout, Alain J. (January 1999). Filtering Knowledge: Changing Information into Knowledge Assets. Journal of Systemic Knowledge Management,. Accessed 01/02/2006

Dobrica Savić

DISCLAIMER: Any views or opinions expressed here are those of the author and do not necessarily reflect those of his employer.