Abstract
Temporal databases provide a complete history of all changes to a database and include the times when changes occurred. This permits users to query the current status of the database as well as the past states, and even future states that are planned to occur. Traditional temporal data models concentrated on describing temporal data based on versioning of objects, tuples or attributes. However, this approach does not effectively manage time-series data that is frequently found in real-world applications, such as sales, economic, and scientific data. In this paper, we first review and formalize a conceptual model that supports time-series objects as well as the traditional version-based objects. The proposed model, called integrated temporal data model (ITDM), is based on EER. It includes in it the concept of time and provides necessary constructs for modeling all different types of objects. We then propose a temporal query language for ITDM, that treats both version-based and time-series data in a uniform manner.
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© 1998 Springer-Verlag Berlin Heidelberg
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Lee, J.Y., Elmasri, R.A. (1998). An EER-Based Conceptual Model and Query Language for Time-Series Data. In: Ling, TW., Ram, S., Li Lee, M. (eds) Conceptual Modeling – ER ’98. ER 1998. Lecture Notes in Computer Science, vol 1507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-49524-6_3
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DOI: https://doi.org/10.1007/978-3-540-49524-6_3
Publisher Name: Springer, Berlin, Heidelberg
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