Computer
The temporal query language TQuel
ACM Transactions on Database Systems (TODS)
On the semantics of “now” in databases
ACM Transactions on Database Systems (TODS)
On the analysis of indexing schemes
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Designing access methods for bitemporal databases
Designing access methods for bitemporal databases
An extensible notation for spatiotemporal index queries
ACM SIGMOD Record
Multidimensional access methods
ACM Computing Surveys (CSUR)
Comparison of access methods for time-evolving data
ACM Computing Surveys (CSUR)
Developing time-oriented database applications in SQL
Developing time-oriented database applications in SQL
IEEE Transactions on Knowledge and Data Engineering
R-Tree Based Indexing of Now-Relative Bitemporal Data
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Light-Weight Indexing of General Bitemporal Data
SSDBM '00 Proceedings of the 12th International Conference on Scientific and Statistical Database Management
Temporal Data and the Relational Model
Temporal Data and the Relational Model
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
Handling of current time in native XML databases
ADC '06 Proceedings of the 17th Australasian Database Conference - Volume 49
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
Proceedings of the ACM international conference companion on Object oriented programming systems languages and applications companion
A methodology for managing database and code changes in a regression testing framework
Proceedings of the 3rd annual conference on Systems, programming, and applications: software for humanity
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 modern database applications contain a significant amount of time dependent data and a substantial proportion of this data is now-relative, i.e. current now. While much research has focussed on indexing temporal data in general, little work has addressed the indexing of now-relative data, which is a natural and meaningful part of every temporal database as well as being the focus of most queries. This paper proposes a logical query transformation that relies on the POINT representation of current time and the geometrical features of spatial access methods. Logical query transformation enables off-the-shelf spatial indexes to be used. We empirically demonstrate that this method is efficient on now-relative bitemporal data, out-performing a straightforward maximum-timestamp approach by a factor of more than 20, both in number of disk accesses and CPU usage.