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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 511))

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Abstract

Temporal database approach is one of the most significant sphere of data processing, the basic part is exact time management, changes and progress monitoring over the time. Conventional database does not support time management, historical data can be processed only partially by difficult and time consuming transformations. Object level principle uses state granularity, thus the whole state is updated, if any attribute value is changed. This approach can be inappropriate, if the frequency and granularity of the changes is not the same and even time varying. This paper deals with object level and attribute level temporal architecture. Usually, data are shared, however, not all data should be accessible to all users, and therefore concept of index definition using contexts is proposed. In terms of efficiency, indexes are restructured using pointer mapping, hybrid context trees are defined.

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Acknowledgment

This publication is the result of the project implementation:

Centre of excellence for systems and services of intelligent transport, ITMS 26220120028 supported by the Research & Development Operational Programme funded by the ERDF and Centre of excellence for systems and services of intelligent transport II., ITMS 26220120050 supported by the Research & Development Operational Programme funded by the ERDF.

This paper is also the result of the project implementation Center of translational medicine, ITMS 26220220021 supported by the Research & Development Operational Programme funded by the ERDF.

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Correspondence to Michal Kvet .

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Kvet, M., Matiaško, K. (2017). Temporal Context Manager. In: Janech, J., Kostolny, J., Gratkowski, T. (eds) Proceedings of the 2015 Federated Conference on Software Development and Object Technologies. SDOT 2015. Advances in Intelligent Systems and Computing, vol 511. Springer, Cham. https://doi.org/10.1007/978-3-319-46535-7_14

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  • DOI: https://doi.org/10.1007/978-3-319-46535-7_14

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