C. Bettini et al., TEMPORAL SEMANTIC ASSUMPTIONS AND THEIR USE IN DATABASES, IEEE transactions on knowledge and data engineering, 10(2), 1998, pp. 277-296
Citations number
28
Categorie Soggetti
Computer Science Artificial Intelligence","Computer Science Information Systems","Engineering, Eletrical & Electronic","Computer Science Artificial Intelligence","Computer Science Information Systems
Data explicitly stored in a temporal database are often associated wit
h certain semantic assumptions. Each assumption can be viewed as a way
of deriving implicit information from explicitly stored data. Rather
than leaving the task of deriving (possibly infinite) implicit data to
application programs, as is the case currently, it is desirable that
this be handled by the database management system. To achieve this, th
is paper formalizes and studies two types of semantic assumptions: poi
nt-based and interval-based. The point-based assumptions include those
assumptions that use interpolation methods over values at different t
ime instants, while the interval-based assumptions include those that
involve the conversion of values across different time granularities.
The paper presents techniques on: 1) how assumptions on specific sets
of attributes can be automatically derived from the specification of i
nterpolation and conversion functions, and 2) given the representation
of assumptions, how a user query can be converted into a system query
such that the answer of this system query over the explicit data is t
he same as that of the user query over the explicit and the implicit d
ata. To precisely illustrate concepts and algorithms, the paper uses a
logic-based abstract query language. The paper also shows how the sam
e concepts can be applied to concrete temporal query languages.