Extending UML for trajectory data warehouses conceptual modelling
J. Wided Oueslati. International Journal of Advanced Computer Science and Applications(IJACSA), (2012)
Abstract
The new positioning and information capture technologies are able to treat data related to moving objects taking place in targeted phenomena. This gave birth to a new data source type called trajectory data (TD) which handle information related to moving objects. Trajectory Data must be integrated in a new data warehouse type called trajectory data warehouse (TDW) that is essential to model and to implement in order to analyze and understand the nature and the behavior of movements of objects in various contexts. However, classical conceptual modeling does not incorporate the specificity of trajectory data due to the complexity of their components that are spatial, temporal and thematic (semantic). For this reason, we focus in this paper on presenting the conceptual modeling of the trajectory data warehouse by defining a new profile using the StarUML extensibility mechanism.
%0 Journal Article
%1 IJACSA.2012.031102
%A Wided Oueslati, Jalel Akaichi
%D 2012
%J International Journal of Advanced Computer Science and Applications(IJACSA)
%K Trajectory UML data data; extension; profile. trajectory warehouse;
%N 11
%T Extending UML for trajectory data warehouses conceptual modelling
%U http://ijacsa.thesai.org/
%V 3
%X The new positioning and information capture technologies are able to treat data related to moving objects taking place in targeted phenomena. This gave birth to a new data source type called trajectory data (TD) which handle information related to moving objects. Trajectory Data must be integrated in a new data warehouse type called trajectory data warehouse (TDW) that is essential to model and to implement in order to analyze and understand the nature and the behavior of movements of objects in various contexts. However, classical conceptual modeling does not incorporate the specificity of trajectory data due to the complexity of their components that are spatial, temporal and thematic (semantic). For this reason, we focus in this paper on presenting the conceptual modeling of the trajectory data warehouse by defining a new profile using the StarUML extensibility mechanism.
@article{IJACSA.2012.031102,
abstract = {The new positioning and information capture technologies are able to treat data related to moving objects taking place in targeted phenomena. This gave birth to a new data source type called trajectory data (TD) which handle information related to moving objects. Trajectory Data must be integrated in a new data warehouse type called trajectory data warehouse (TDW) that is essential to model and to implement in order to analyze and understand the nature and the behavior of movements of objects in various contexts. However, classical conceptual modeling does not incorporate the specificity of trajectory data due to the complexity of their components that are spatial, temporal and thematic (semantic). For this reason, we focus in this paper on presenting the conceptual modeling of the trajectory data warehouse by defining a new profile using the StarUML extensibility mechanism.},
added-at = {2014-02-21T08:00:08.000+0100},
author = {{Wided Oueslati}, Jalel Akaichi},
biburl = {https://www.bibsonomy.org/bibtex/26b79892e57da06895ccac92523901a80/thesaiorg},
interhash = {2999891fce475b866dafbb85d5b09388},
intrahash = {6b79892e57da06895ccac92523901a80},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA)},
keywords = {Trajectory UML data data; extension; profile. trajectory warehouse;},
number = 11,
timestamp = {2014-02-21T08:00:08.000+0100},
title = {{Extending UML for trajectory data warehouses conceptual modelling}},
url = {http://ijacsa.thesai.org/},
volume = 3,
year = 2012
}