Different roles and mutual dependencies of data, information, and knowledge — An AI perspective on their integration |
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Authors: | Agnar Aamodt Mads Nygrd |
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Affiliation: | a University of Trondheim, Department of Informatics, N-7055, Dragvoll, Norway b Sintef Delab, Database Technology Group, N-7034, Trondheim, Norway |
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Abstract: | The unclear distinction between data, information, and knowledge has impaired their combination and utilization for the development of integrated systems. There is need for a unified definitional model of data, information, and knowledge based on their roles in computational and cognitive information processing. An attempt to clarify these basic notions is made, and a conceptual framework for integration is suggested by focusing on their different roles and frames of reference within a decision-making process. On this basis, ways of integrating the functionalities of databases, information systems and knowledge-based systems are discussed by taking a knowledge level perspective to the analysis and modeling of systems behaviour. Motivated by recent work in the area of case-based reasoning related to decision support systems, it is further shown that a specific problem solving episode, or case, may be viewed as data, information, or knowledge, depending on its role in decision making and learning from experience. An outline of a case-based system architecture is presented, and used to show that a focus on the retaining and reuse of past cases facilitates a gradual and evolutionary transition from an information system to a knowledge-based system. |
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Keywords: | Integrated systems Knowledge modeling Machine learning Case-based reasoning |
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