The 2-3TR-tree, a trajectory-oriented index structure for fully evolving valid-time spatio-temporal datasets Mahdi Abdelguerfi, Julie Givaudan, Kevin Shaw, and Roy Ladner   View Paper (PDF)   Return to Spatio-temporal data handling Abstract Supporting large volumes of multi-dimensional data is an inherent characteristic of modern database applications, such as Geographical Information Systems (GIS), Computer Aided design (CAD), and Image and Multimedia Databases. Such databases need underlying systems with extended features like query languages, data models, and indexing methods, as compared to traditional databases, mainly because of the complexity of representing and retrieving data. The presented work deals with access methods for databases that accurately model the real world. More precisely, the focus is on index structures that can capture the time varying nature of moving objects, namely spatio-temporal structures. A new taxonomy to classify these structures has been defined according to dataset characteristics and query requirements. Then, a new spatio-temporal access method, the 2-3TR-tree, has been designed to process specific datasets and fulfill specific query requirements that no other existing spatio-temporal index could handle. DiSC'03 © 2003 Association for Computing Machinery