Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Temporal Databases

View through CrossRef
AbstractA temporal database stores time‐varying data and has the capabilities to manipulate it. Two commonly used time dimensions for maintaining temporal data are valid time and transaction time. Temporal databases are classified as valid time, transaction time, or bitmeporal databases. Temporality in databases involve subtle issues like comparing database states at different times, temporal grouping, different ways to represent the same temporal data, consistency of the timestamps of different attributes, temporal integrity constraints, and designing temporal databases. A temporal atom is a timestamp and value pair in which The timestamp is valid and/or transaction time and value are the time‐varying data. For representing and manipulating temporal data, data models handle temporal atoms differently. In relational data model, which is the focus of this entry, attribute or tuple time stamping may be used. Temporal algebra and temporal calculus languages are defined accordingly. Proposals for extending SQL2 for temporal data manipulation exist, and SQl3 supports user‐defined data types that can be used for defining and manipulating temporal data. This entry covers temporal query languages and the temporal issues mentioned above.
Title: Temporal Databases
Description:
AbstractA temporal database stores time‐varying data and has the capabilities to manipulate it.
Two commonly used time dimensions for maintaining temporal data are valid time and transaction time.
Temporal databases are classified as valid time, transaction time, or bitmeporal databases.
Temporality in databases involve subtle issues like comparing database states at different times, temporal grouping, different ways to represent the same temporal data, consistency of the timestamps of different attributes, temporal integrity constraints, and designing temporal databases.
A temporal atom is a timestamp and value pair in which The timestamp is valid and/or transaction time and value are the time‐varying data.
For representing and manipulating temporal data, data models handle temporal atoms differently.
In relational data model, which is the focus of this entry, attribute or tuple time stamping may be used.
Temporal algebra and temporal calculus languages are defined accordingly.
Proposals for extending SQL2 for temporal data manipulation exist, and SQl3 supports user‐defined data types that can be used for defining and manipulating temporal data.
This entry covers temporal query languages and the temporal issues mentioned above.

Related Results

Role of the Frontal Lobes in the Propagation of Mesial Temporal Lobe Seizures
Role of the Frontal Lobes in the Propagation of Mesial Temporal Lobe Seizures
Summary: The depth ictal electroencephalographic (EEG) propagation sequence accompanying 78 complex partial seizures of mesial temporal origin was reviewed in 24 patients (15 from...
Hydatid Disease of The Brain Parenchyma: A Systematic Review
Hydatid Disease of The Brain Parenchyma: A Systematic Review
Abstarct Introduction Isolated brain hydatid disease (BHD) is an extremely rare form of echinococcosis. A prompt and timely diagnosis is a crucial step in disease management. This ...
New approaches in developing medicinal herbs databases
New approaches in developing medicinal herbs databases
Abstract Medicinal herbs databases have become a crucial part of organizing new scientific literature generated in medicinal herbs field, as well as new drug discove...
Managing Temporal Data
Managing Temporal Data
In general, databases store current data. However,the capability to maintain temporal data is a crucial requirement for many organizations and provides the base for organizational ...
Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models
Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models
State variables such as abundance and occurrence of species are central to many questions in ecology and conservation, but our ability to detect and enumerate species is imperfect ...
Temporal Extension for a Conceptual Multidimensional Model
Temporal Extension for a Conceptual Multidimensional Model
Data warehouses integrate data from different source systems to support the decision process of users at different management levels. Data warehouses rely on a multidimensional vie...

Back to Top