Abstract
Approximate representation of any spatio-temporal variable, by some interpolation function, is necessary when it is measured only sporadically. This paper argues that the approximate representation can be captured by a constraint database. Since constraint databases can be queried via standard query languages - such as relational algebra, SQL and Datalog - this provides an immediate benefit for flexible querying of the data. We propose a concrete system that implements a version of this approach. We also add beyond the standard queries new ones like cartogram similarity queries and an advanced graphical user interface with 3-D animation of GIS-based data.
This work was supported in part by NSF grants IRI-9625055 and IRI-9632871 and by a Gallup Research Professorship.
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Chen, R., Ouyang, M., Revesz, P.Z. (2000). Approximating Data in Constraint Databases. In: Choueiry, B.Y., Walsh, T. (eds) Abstraction, Reformulation, and Approximation. SARA 2000. Lecture Notes in Computer Science(), vol 1864. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44914-0_8
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