This is not trivial. These are not to be confused with each other either. But it’s a difficult matter, I agree to as much. With this article I am trying to share as much as I know about data, information, knowledge and wisdom and explain the differences.
First we are going to have a look at each of components on their own and as we progress, we will identify what ties them together and what differentiates them from each other. Let’s start with the basest entity of wisdom – data.
What is data?
The term ‘data’ is related to the Latin word ‘datum’ which means “something given”. Nowadays when people talk about data, they are talking about values of quantitative or qualitative variables. Data itself usually does not indicate a particular meaning and it does not add a positive, negative or neutral meaning to the value itself.
Example: An engineer writes “5” down in a notebook.
What is information?
The word ‘information’ is related to the Latin verb ‘informare’, which in a sense means “to instruct”, “to teach” or more directly “to inform”. Information is usually the answer to a question. When data is brought into context, within the comprehension of a cognitive observer, it becomes an information.
Example: The engineer writes down, “Vehicle requires 5 gallons of fuel to go 100 miles”.
What is knowledge?
Knowledge is the awareness of data brought into relation to form information in a wider sense. Knowledge is supported by experience and other forms of education and learning to comprehend the relationship of data to information and both their reason and meaning. Knowledge acquisition involves complex cognitive processes, such as perception, communication and reasoning.
Example: The engineer writes down, “The vehicle requires more fuel than what the statistical average is”.
What is wisdom?
Wisdom is not the capacity of what you know. Wisdom is the ability to think and act using knowledge and this process is supported by intellect and capacity for logic. Wisdom is what you know, what you understand and what you comprehend along with both implicit and explicit relationships of provided data, information and knowledge. Beyond reasoning, wisdom also includes clear understanding of cause and effect of a concept.
Example: The engineer reports to a supervisor, “If we want to make the vehicle competitive, we need to improve the fuel consumption ratio to travelled distance”.
The DIKW model
Even though many people use these terms as if they were the same thing, actually they are all parts of a rather abstract concept and are not interchangeable. The relationship model that ties these terms together is frequently labeled as “DIKW model”.
As this is a sphere, that does not easily allow for proof and evidence, the DIKW model is sometimes disputed. Do you feel something is terribly off here or do you have any other thoughts to share on the matter? Please use the comment section below. I am looking forward to hear from you!
If you’d like to read more about these subjects you can check out these books with more information. Will they become part of your knowledge? 😉
Photo credit: NASA Goddard Space Flight Center
Hi there and thanks for reading my article! I’m Chris the founder of TechAcute. I write about technology news and share experiences from my life in the enterprise world. Drop by on Twitter and say ‘hi’ sometime. 😉