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Disentangling data, information and knowledge

Computer Science Trust Fund Endowed Eminent Scholar School of Computing & Informatics, University of Louisiana at Lafayette Lafayette, Louisiana 70504, USA

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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Keywords Information; data; knowledge; science; computer programming; cognitive science; philosophy; symbol structures

Citation: Subrata Dasgupta. Disentangling data, information and knowledge. Big Data and Information Analytics, 2016, 1(4): 377-390. doi: 10.3934/bdia.2016016


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Copyright Info: 2016, Subrata Dasgupta, licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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