TY - JOUR
T1 - Spatiotemporal aggregate computation
T2 - A survey
AU - López, Inés Fernando Vega
AU - Snodgrass, Richard T.
AU - Moon, Bongki
N1 - Funding Information:
This work was sponsored in part by US National Science Foundation (NSF) Grant No. IIS-0100436 and NSF Research Infrastructure Program EIA-0080123. It was also supported in part by the Mexican Foundation for Science and Technology (CONACyT), scholarship 117476. The authors assume all responsibility for the contents of the paper.
PY - 2005/2
Y1 - 2005/2
N2 - Spatiotemporal databases are becoming increasingly more common. Typically, applications modeling spatiotemporal objects need to process vast amounts of data. In such cases, generating aggregate information from the data set is more useful than individually analyzing every entry. In this paper, we study the most relevant techniques for the evaluation of aggregate queries on spatial, temporal, and spatiotemporal data. We also present a model that reduces the evaluation of aggregate queries to the problem of selecting qualifying tuples and the grouping of these tuples into collections on which an aggregate function is to be applied. This model give us a framework that allows us to analyze and compare the different existing techniques for the evaluation of aggregate queries. At the same time, it allows us to identify opportunities for research on types of aggregate queries that have not been studied.
AB - Spatiotemporal databases are becoming increasingly more common. Typically, applications modeling spatiotemporal objects need to process vast amounts of data. In such cases, generating aggregate information from the data set is more useful than individually analyzing every entry. In this paper, we study the most relevant techniques for the evaluation of aggregate queries on spatial, temporal, and spatiotemporal data. We also present a model that reduces the evaluation of aggregate queries to the problem of selecting qualifying tuples and the grouping of these tuples into collections on which an aggregate function is to be applied. This model give us a framework that allows us to analyze and compare the different existing techniques for the evaluation of aggregate queries. At the same time, it allows us to identify opportunities for research on types of aggregate queries that have not been studied.
KW - Aggregate function
KW - Aggregation queries
KW - Spatiotemporal databases
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U2 - 10.1109/TKDE.2005.34
DO - 10.1109/TKDE.2005.34
M3 - Article
AN - SCOPUS:14644390243
SN - 1041-4347
VL - 17
SP - 271
EP - 286
JO - IEEE Transactions on Knowledge and Data Engineering
JF - IEEE Transactions on Knowledge and Data Engineering
IS - 2
ER -