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Managing Rigid Temporal Geometries in Moving Object Databases

par Schoemans, Maxime
Président du jury Roland, Jérémie
Promoteur Sakr, Mahmoud
Co-Promoteur Zimanyi, Esteban
Publication Non publié, 2025-02-25

Thèse de doctorat

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Résumé :

Temporal geometries, also called moving objects, are objects whose geometrical representation evolves over time. Various applications process geospatial trajectories of moving objects, such as cars, ships and robots. There is thus a need for a common conceptual framework to model and manage these objects, as well as to enable data interoperability across tools. The International Organization for Standardization ISO has responded to this need and created the standard ISO 19141--Schema for moving features. Among its types, it defines a schema for rigid temporal geometries, which represent the movement of spatial objects translating and rotating over time, while preserving a fixed shape. Despite the abundance of these objects in real-world, there exists no reference implementation of this type of data in a common system, which causes them to usually be represented as temporal points without taking into account their spatial extents and shapes.The objective of the thesis is to investigate the problem of modeling and querying rigid temporal geometries in moving object databases, with the ultimate goal to achieve an implementation of respective data types, functions, operators and indexing capabilities in the MobilityDB open-source database. Additionally, we present a tool to visualize temporal geometries stored in a database. Specifically, the four main contributions of this thesis are as follows: (1) We propose a new data model for rigid temporal geometries, alongside efficient algorithms for the operations defined in ISO~19141. This model is implemented within MobilityDB, a moving object database extension for PostgreSQL, enabling robust and efficient handling of temporal geometries. Additionally, we review the ISO~19141 standard from an implementation perspective, providing insights for potential improvements. (2) An efficient algorithm is developed for computing the temporal distance between moving bodies and other static or moving geometries. This approach extends the V-Clip and Lin-Canny closest features algorithms from computational geometry, allowing for accurate tracking of the temporal evolution of closest feature pairs in moving objects. (3) We introduce MGiST and MSP-GiST, multi-entry generalized search trees based on the GiST and SP-GiST structures. These new search trees are designed to partition objects into multiple entries upon insertion, enhancing search performance. Evaluated in a trajectory indexing scenario, these techniques yield up to an order-of-magnitude improvement in point, range, and nearest-neighbor query performance. (4) MOVE (Moving Objects Visual Exploration), an open-source visualization tool, is presented as an integration of MobilityDB with QGIS. This tool allows users to query and visualize moving object data through a straightforward interface, supporting both static and animated visualizations within QGIS and enhancing the accessibility of spatial-temporal data. Each section of this thesis is implemented and published as open-source. The data types and operations, including the temporal distance function, are implemented in MobilityDB. MGiST and MSP-GiST are implemented as new access methods for PostgreSQL and packaged into a stand-alone extension called mest (Multi-Entry Search Trees). Instantiations of these access methods for trajectory indexing are implemented in a second extension, called mobilitydb_mest. Lastly, MOVE is implemented as a Python QGIS extension and published on the QGIS Python Plugins Repository.