Computer
The temporal query language TQuel
ACM Transactions on Database Systems (TODS)
The design and analysis of spatial data structures
The design and analysis of spatial data structures
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
On the semantics of “now” in databases
ACM Transactions on Database Systems (TODS)
An extensible notation for spatiotemporal index queries
ACM SIGMOD Record
Comparison of access methods for time-evolving data
ACM Computing Surveys (CSUR)
The TSQL2 Temporal Query Language
The TSQL2 Temporal Query Language
Indexing Techniques for Advanced Database Systems
Indexing Techniques for Advanced Database Systems
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Designing Access Methods for Bitemporal Databases
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Indexing Valid Time Databases via B+-Trees
IEEE Transactions on Knowledge and Data Engineering
The Effect of Buffering on the Performance of R-Trees
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
R-Tree Based Indexing of Now-Relative Bitemporal Data
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Hilbert R-tree: An Improved R-tree using Fractals
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Generalized Search Trees for Database Systems
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Access Methods for Bi-Temporal Databases
Proceedings of the International Workshop on Temporal Databases: Recent Advances in Temporal Databases
M-IVTT: An Index for Bitemporal Databases
DEXA '96 Proceedings of the 7th International Conference on Database and Expert Systems Applications
Developing a DataBlade for a New Index
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Indexing of now-relative spatio-bitemporal data
The VLDB Journal — The International Journal on Very Large Data Bases
An efficient method for indexing now-relative bitemporal data
ADC '04 Proceedings of the 15th Australasian database conference - Volume 27
Modification semantics in now-relative databases
Information Systems
The POINT approach to represent now in bitemporal databases
Journal of Intelligent Information Systems
BiB+-tree: an efficient multiversion access method for bitemporal databases
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
A triangular decomposition access method for temporal data - TD-tree
ADC '11 Proceedings of the Twenty-Second Australasian Database Conference - Volume 115
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Most data managed by existing, real-world database applications is time referenced. Often, two temporal aspects of data are of interest, namely valid time, when data is true in the mini-world, and transaction time, when data is current in the database, resulting in so-called bitemporal data. Like spatial data, bitemporal data thus has associated two-dimensional regions. Such data is in part naturally now relative: some data is true until the current time, and some data is part of the current database state. Therefore, unlike for spatial data, bitemporal data regions may grow continuously. Existing indices, e.g., B+- and R-trees, typically do not contend well with even small amounts of now-relative data.In contrast, the 4-R index presented in the paper is capable of indexing general bitemporal data efficiently. The different kinds of growing data regions are transformed into stationary regions, which are then indexed by R*-trees. Queries are also transformed to counter the data transformations, yielding a technique with perfect precision and recall. Performance studies indicate that the technique is competitive with the best existing index; and unlike this existing index, the new technique does not require extension of the DBMS kernel.