Abstract
Most spatial information systems are limited to a fixed dimension (generally 2) which is not extensible. On the other hand, the emerging paradigm of constraint databases allows the representation of data of arbitrary dimension, together with abstract query languages. The complexity of evaluating queries though might be costly if the dimension of the objects is really arbitrary. In this paper, we present a data model, based on linear constraints, dedicated to the representation and manipulation of multidimensional data. In order to preserve a low complexity for query evaluation, we restrict the orthographic dimension of an object O, defined as the dimension of the components O_{1},\ldots,O_{n} such that O=O_{1}\times\cdots\times O_{n}. This allows to process queries independently on each component, therefore achieving a satisfying trade-off between design simplicity, expressive power of the query language and efficiency of query evaluation. We illustrate these concepts in the context of spatio-temporal databases where space and time are the natural components. This data model has been implemented in the DEDALE system and a spatio-temporal application, with orthographic dimension 2, is currently running, thus showing the practical relevance of the approach.
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