Most of computer science is built on top of Claude Shannon’s “Information Theory”. Observers have noted that ‘computer science’ has very little to do with computers. I have come to think of it as ‘computation and information science’. I might throw in the word “process” to bind everything together, if I could work out where to put it. For a long time I was ready to dismiss the word “science” but I have recently changed my mind.
In the book I’m writing, I plan to point out that Shannon explicitly says in his paper that he and his theory don’t care about the meaning of any signal being transmitted. It could be meaningless. To my mind that is data not information. Our foundations are shaky.
There is a long tradition of drawing a triangle with layers labelled ‘data’, ‘information’ and ‘knowledge’. Here is one: http://www.knowledge-management-tools.net/knowledge-information-data.html
I am trying to develop my own model that adds layers and explains the difference between them. My working definition of the difference between data and information is that information requires a cultural context to be understood. I tried to think of the simplest information I’d ever seen. It was 3 sticks laid down on a forest path, to make an arrow shape (or they fell randomly from a tree. Here, Shannon has something useful to say.) I realised that interpreting this arrow requires a knowledge of human weapons technology. Recognising whether an arrow symbol on a path is a message also requires environmental, cultural and statistical knowledge.
I only came up with my distinction between information and knowledge a few days ago, so I’ll keep testing my hypothesis until the book comes out. I will say that I don’t believe you can store knowledge in a computer system. Oh dear, someone else beat me to the ‘wisdom layer’: http://plmindia.com/services/knowledge-management/