Abstract

A large amount of data resulting from trajectories of moving objects activities are collected from various localization based services and some associated automated processes. This Trajectories data can be used either for transaction and analysis purposes in various domains (commerce, environment, migration of bird, etc.). For this reason, modeling trajectory data at the conceptual level is an important step leading for successful implementations. current modeling tools fail to fulfill specific moving objects activities requirements. In this paper, it propose a new profile based on UML to enhance the conceptual modeling of trajectory data related to mobile objects by new stereotypes and icons. As illustration, it present a mobile hotal use case.

References

• S .Spaccapietra., C. Parent, M. L. Damiani, J. A. de Macedo, F. Porto, C. Vangenot. A Conceptual View on Trajectories. Research Report. Ecole Polytechnique Fédérale, Database Laboratory, Lausane, Switzerland. May, 29th, 2007.
• J .Fernando. Braz. “Trajectory data warehouse proposal of design and application to exploit data”. IX Brazilian Symposium on GeoInformatics, Campos do Jordão, Brazil, November 25-28, 2007, INPE, p 61-72. 2007.
• J .Trujillo., M. Palomar et J. Gomez, I.Y. Song. “Designing data warehouses with OO conceptualmodels”. IEEE Computer 34 (12) 66–75 (Special issue on Data Warehouses). 2001
• S .Brakatsoulas., D. Pfoser, and N. Tryfona. Modeling, storing and mining moving objects databases. In International Database Engineering and Applications Symposium (IDEAS), pp. 68-77, 2004.
• I.Sandu Popa,Ahmed Kharrat Karine Zeitouni. « CALM – Un système de gestion de données de capteurs à Localisation Mobile ». Conférence SAGEO. 2008.
• A .Bouju., F. Bertrand, V. Mallé-Noyon, S. Servigne, T. Devogele, C. Ray, H Martin et J. Gensel. « Gestion de données spatio-temporelles au sein de bases de données capteurs ». Conférence sur les Technologies de l’Information, de la Communication et de la Géolocalisation dans les Systèmes de Transports Bretagne. 2009.
• E. Gaudreau, Bruno Agard, Martin Trepanier et Pierre Baptiste. « Pilotage réactif des systèmes de production à l'aide de capteurs intelligents ». 6e Congrès international de génie industriel- Besançon (France). 7-10 juin 2005.
• S. Orlando, Renzo Orsini, Alessandra Raffaetà, Alessandro Roncato and Claudio Silvestri. “Trajectory Data Warehouses: Design and Implementation Issues”. Jitnal of computing science and engineering, vol.1, no.2, pages 211-232. 2007.
• X .Meng. Z. Ding. “DSTTMOD: A Discrete Spatio- TemporalTrajectory Based Moving Object Databases System”. LNCS 2736, (Springer verlag). 2003
• S. Lujàn-Mora, Juan Trujillo et Il-Yeol Song. “A UML profile for multidimensional modelling in datawarehouses”. Data & Knowledge Engineering (DKE), 59(3), 725-769. 2006.
• G .Pestana. M. Mira da Silva. “Multidimensional Modeling Based on Spatial, Temporal and Spatio-Temporal Stereotypes”. ESRI International User Conference San Diego Convention Center, California. 2005.
• M .Miquel. Bedard Yvan. « Conception d’entrepôts de données géo spatiales à partir de sitces hétérogènes ». Exemple d’application en foresterie. Ingénierie des systèmes d’information, pages 89-111. 2002.
• S. Nebojsa, Han Jiaiti et Kosperski Krzysztof. “Object- Based Selective Materialization for Efficient Implementation of Spatial Data Cubes”. IEEE Transactions on Knowledge and Data Engineering, Vol. 12, n° 6, p 938-958. 2000.
• W .Oueslati., J. Akaichi. Mobile information collectors' trajectory data warehouse design. International jitnal of managing information technologies. P 1-20,2010.
• C .Parent., S. Spaccapietra and E. Zimanyi. Conceptual Modeling for Traditional and Spatio-Temporal Applications - The MADS Approach. In Springer Verlag,2006.