Pattern languages of program design
Pattern languages of program design
An open abstract-object storage system
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Multidimensional access methods
ACM Computing Surveys (CSUR)
ACM Computing Surveys (CSUR)
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The DASDBS Project: Objectives, Experiences, and Future Prospects
IEEE Transactions on Knowledge and Data Engineering
The Implementation of POSTGRES
IEEE Transactions on Knowledge and Data Engineering
Starburst Mid-Flight: As the Dust Clears
IEEE Transactions on Knowledge and Data Engineering
Inclusion of New Types in Relational Data Base Systems
Proceedings of the Second International Conference on Data Engineering
VLDB '87 Proceedings of the 13th 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
Physical Database Design for Raster Images in CONCERT
SSD '97 Proceedings of the 5th International Symposium on Advances in Spatial Databases
Plug and Play: Interoperability in CONCERT
INTEROP '99 Proceedings of the Second International Conference on Interoperating Geographic Information Systems
Buffering Long Externally-Defined Objects
Proceedings of the Sixth International Workshop on Persistent Object Systems
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In this paper we present the prototype database system CONCERT and the incorporation of a framework of a generic index tree for spatio-temporal data. We show the ideas behind the Concert architecture as far as they are important to understand the framework approach presented. We show how the index is based on the conceptual behaviour of data in contrast to generalized algorithms or methods. Because of the simplicity of R-trees we take an R-tree like structure to explain our generic spatio-temporal index. It is remarkable that in CONCERT a generic index can be defined without any predefined "hard-wired" spatial or temporal data types such as intervals or rectangles. As it turns out the only important properties needed are an OVERLAP and a SPLIT function, the first one checking for spatial or temporal overlap of objects, the second one providing a hierarchical decomposition of the data space into subspaces. If, in addition, splitting of data objects is allowed we are able to define manageable node sizes, leading to an improved generic index similar to R+-trees or other derivations.