Information, data and knowledge constitute the fundamental ‘stuff’ of computing and one might assume that in the seven decades since the advent of the modern computer theorists and practitioners of computing can differentiate between the concepts they denote. And, of course, computer scientists do not have exclusive claims over these terms or concepts:sociologists, cultural scholars, economists, historians, natural scientists, philosophers, and the managerial class have them as part of their vocabularies. The surprising fact is that these terms and the concepts they denote are far from distinct. They form a tangled web. In this essay I address the question:what is the relationship between data, information and knowledge? I attempt to disentangle-and clarify-how these terms are in fact interpreted by practitioners in such diverse disciplines as information science, historical research, empirical sciences, cognitive science, data mining and computer programming and to identify what appears to be a common thread.
Citation: Subrata Dasgupta. Disentangling data, information and knowledge[J]. Big Data and Information Analytics, 2016, 1(4): 377-390. doi: 10.3934/bdia.2016016
Abstract
Information, data and knowledge constitute the fundamental ‘stuff’ of computing and one might assume that in the seven decades since the advent of the modern computer theorists and practitioners of computing can differentiate between the concepts they denote. And, of course, computer scientists do not have exclusive claims over these terms or concepts:sociologists, cultural scholars, economists, historians, natural scientists, philosophers, and the managerial class have them as part of their vocabularies. The surprising fact is that these terms and the concepts they denote are far from distinct. They form a tangled web. In this essay I address the question:what is the relationship between data, information and knowledge? I attempt to disentangle-and clarify-how these terms are in fact interpreted by practitioners in such diverse disciplines as information science, historical research, empirical sciences, cognitive science, data mining and computer programming and to identify what appears to be a common thread.
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