Temporal information plays a crucial role in medicine, so that in Medical Informatics there is an increasing awareness that suitable database approaches are needed to store and support it. Specifically, a great amount of clinical data (e.g., therapeutic data) are periodically repeated. Although an explicit treatment is possible in most cases, it causes severe storage and disk I/O problems. In this paper, we propose an innovative approach to cope with periodic medical data in an implicit way. We propose a new data model, representing periodic data in a compact (implicit) way, which is a consistent extension of TSQL2 consensus approach. Then, we identify some important types of temporal queries, and present query answering algorithms to answer them. We also sketch a temporal relatiol algebra for our approach. Filly, we show experimentally that our approach outperforms current explicit approaches.
13th World Congress on Medical Informatics (Medinfo 2010) (2010)
Cape Town, South Africa
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