期刊
COMPUTER SCIENCE REVIEW
卷 47, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.cosrev.2022.100516
关键词
Moving object; Moving point; Moving region; Trajectory data; Trajectory data warehouse; Conceptual modeling; Ontological modeling
This paper investigates the literature on moving objects, trajectory data, and trajectory data warehouse modeling, and compares classical and ontological existing patterns. Through this research, the strong and limited contributions of these patterns are demonstrated.
The development of mobile technologies has paved the way for new and various applications taking advantage of trajectory data resulting from moving objects activities in their associated ecosystems. Such data can be mainly handled either by real time applications or by oriented decision-making tools going from trajectory data warehouse technology to data mining classical advanced instruments. Indeed, applications dealing with moving objects encompass hidden significant knowledge that can be made visible through analytical and mining tools. This precious knowledge could not come properly in hands only if, the trajectory data problem modeling is global, precise, and concise. The aim of this paper is to investigate the appropriate literature on moving objects, trajectory data, and trajectory data warehouse modeling going from classical to ontological existing patterns. A comparison will be made between them, through which strong and limited contributions will be shown. This work aims to be valuable for researchers aiming to select and use modeling approaches in mobile objects ecosystems. (c) 2022 Elsevier Inc. All rights reserved.
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