A. Sekar and A.H. Lee (USA)
Data modeling, geospatial data, and metamodeling
In the last decade, the amount of geospatial data collected
has been phenomenal. Each day terabytes of data are
collected by government and commercial data providers
using everything from inexpensive handheld GPS devices
to complex satellite systems. Using these data, however,
is proving to be costly and difficult. Because of the
diversity in the types of geospatial data and the different
ways they are used, creating standards for the
organization of this data has seemed intractable. In this
paper, we take a more global approach to this problem.
By examining the fundamental structure of all geospatial
data and by breaking down all the processes of using
these data to a few basic operations, we create a
framework for data models which can be used to
represent any geospatial data and allows for the efficient
use (and reuse) of these data. A metamodeling approach
using two meta-layers is used to define this framework.
This approach facilitates the creation of systems that are
data model agile.