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Generational analysis of tension and entropy in data structures: impact on automatic data integration and on the semantic web

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Abstract

The move toward automatic data integration from autonomous and heterogeneous sources is viewed as a transition from a closed to an open system, which is in essence an adaptive information processing system. Data definition languages from various computing eras spanning almost 50 years to date are examined, assessing if they have moved from closed systems to open systems paradigm. The study proves that contemporary data definition languages are indistinguishable from older ones using measurements of Variety, Tension and Entropy, three characteristics of complex adaptive systems (CAS). The conclusion is that even contemporary data definition languages designed for such integration exhibit closed systems characteristics along with open systems aspirations only. Plenty of good will is insufficient to make them more suitable for automatic data integration than their oldest predecessors. A previous report and these new findings set the stage for the development and proposal of a mathematically sound data definition language based on CAS, thus potentially making it better suited for automatic data integration from autonomous heterogeneous sources.

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    Eli Rohn

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Rohn, E. Generational analysis of tension and entropy in data structures: impact on automatic data integration and on the semantic web. Knowl Inf Syst 28, 175–196 (2011). https://doi.org/10.1007/s10115-010-0314-z

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