A widely held view amongst computer scientists is that the fundamental stuff of computer science is information.

What such meaningful information shares with meaningless information, as computer scientist Paul Rosenbloom has noted, is that it must be expressed in some physical medium such as electrical signals, magnetic states, or marks on paper; and that it resolves uncertainty.

Hierarchical organization, he stated, is a means of managing the complexity of an entity.

AI researchers may well claim that what they do, in their branch of computer science, is knowledge

Even the ‘meaningless’ information of information theory, the bits and bytes, are represented by physical symbols within a computer, such as voltage levels or magnetic states, or on paper by strings of 0s and 1s.

Luciano Floridi, a philosopher of computing, offered the following view of the information/knowledge nexus. Information and knowledge bear a ‘family resemblance’. They are both meaningful entities but they differ in that

compositional hierarchy.

So according to Ackoff, contra Knuth, data precedes information.

Computer science is, ultimately, the science of automatic symbol processing, an insight which Allen Newell and Herbert Simon have emphasized.