The temporal query language TQuel
ACM Transactions on Database Systems (TODS)
Logical modeling of temporal data
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Event-join optimization in temporal relational databases
VLDB '89 Proceedings of the 15th international conference on Very large data bases
Developing time-oriented database applications in SQL
Developing time-oriented database applications in SQL
Database System Concepts
The Historical Relational Data Model (HRDM) and Algebra Based on Lifespans
Proceedings of the Third International Conference on Data Engineering
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
A Framework for Query Optimization in Temporal Databases
Proceedings of the 5th International Conference SSDBM on Statistical and Scientific Database Management
A feature-based linear data model supported by temporal dynamic segmentation
A feature-based linear data model supported by temporal dynamic segmentation
A spatiotemporal data model for dynamic transit networks
International Journal of Geographical Information Science
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In recent years, there have been many research studies focusing on linear data modeling as well as on temporal GIS-T (GIS for transportation) implementations. However, what was fundamentally missing from the research circle was the study of a methodology for processing and representation of linearly referenced features in the temporal context, or temporal dynamic segmentation. This paper dissects the functional specifications of temporal dynamic segmentation. The authors start by exploring the definition and characteristics of dynamic segmentation. The scope of dynamic segmentation is extended to include two functional categories and three essential functions. The paper then defines spatiotemporal segment and a spatiotemporal join operation, which are the building blocks and the key mechanism behind temporal dynamic segmentation. A set of metric criteria for identifying spatiotemporal segment topologies are proposed as an effective alternative to the more general, but more costly, frameworks for the identification of topological relationships. The authors finally present functional specifications of the three essential functions of dynamic segmentation.