A General Approach to Represent and Query Now-Relative Medical Data in Relational Databases
Author(s)
Anselma, Luca
Piovesan, Luca
Sattar, Abdul
Stantic, Bela
Terenziani, Paolo
Year published
2015
Metadata
Show full item recordAbstract
Now-related temporal data play an important role in the medical context. Current relational temporal database (TDB) approaches are limited since (i) they (implicitly) assume that the span of time occurring between the time when facts change in the world and the time when the changes are recorded in the database is exactly known, and (ii) do not explicitly provide an extended relational algebra to query now-related data. We propose an approach that, widely adopting AI symbolic manipulation techniques, overcomes the above limitations.Now-related temporal data play an important role in the medical context. Current relational temporal database (TDB) approaches are limited since (i) they (implicitly) assume that the span of time occurring between the time when facts change in the world and the time when the changes are recorded in the database is exactly known, and (ii) do not explicitly provide an extended relational algebra to query now-related data. We propose an approach that, widely adopting AI symbolic manipulation techniques, overcomes the above limitations.
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Journal Title
Lecture Notes in Computer Science
Volume
9105
Subject
Other information and computing sciences not elsewhere classified