Towards an implicit treatment of periodically-repeated medical data.
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 relational algebra for our approach. Finally, we show experimentally that our approach outperforms current explicit approaches.
Stantic
Bela
B
Institute for Integrated and Intelligent Systems, Griffith Univ., Queensland, Australia.
Terenziani
Paolo
P
Sattar
Abdul
A
Bottrighi
Alessio
A
Governatori
Guido
G
D000465:Algorithms; D016208:Databases, Factual; D016247:Information Storage and Retrieval / Q000379:methods; D008490:Medical Informatics; D016347:Medical Records Systems, Computerized