In the world of data and fact-based modelling, the terms 'knowledge', 'data' and 'information' are widely used. These concepts have many similarities, but there are also some essential differences. Often, these terms are mistakenly confused. In this article, we explain the differences between knowledge, data and information.
When you talk about data, the buzz words fly around your ears. Big data, AI, smart data! But what is data really? Data are the physical representations of facts; data are numbers, graphs, text or images. Things like sound clips or videos are also data.
Information is almost identical to data, only there is one big difference: information has context, it is qualified. Data, by itself, has no context and therefore no value. Without context, a worksheet full of numbers is simply an accumulation of meaningless numbers.
Knowledge is a much broader concept than data or information. Information is a part of knowledge, but knowledge is also strongly connected to persons. With the help of knowledge a person can use certain information. Information is an instructional text that explains how a physiotherapist should massage a certain muscle group, knowledge is the ability to apply this information in practice. Knowledge is the sum of information, the understanding of information and personal skills.
This difference is easily illustrated by an example:
This graph consists of data. It is a series of numbers set against another series of numbers. You have no idea what it means or what you can do with it.
Now look at the difference with the graph below.
This is information because there is a clear context. The axes are qualified as age and height. The data represent the growth of the person Emma van Dijk. Her height in centimetres is plotted against her age in years.
A caregiver then has the knowledge to use this information. Because of their training and practical experience with growing children, they can make a prognosis for Emma's further growth course.
Knowledge, data and information are thus related concepts, but the differences are significant. Data is the basis, information is the context and knowledge is the application.