Аннотация
Integrating spatial datasets from diverse sources is essential for
cross-border environmental investigations and decision-making. This
is a little investigated topic that has profound implications for
the availability and reliability of spatial data. At present, ground-water
hydrostratigraphic models exist for both the Canadian or for the
United States (U.S.) portion of the aquifer but few are integrated
across the border. In this paper, we describe the challenges of integrating
multiple source, large datasets for development of a groundwater
hydrostratigraphic model for the Abbotsford-Sumas Aquifer. Growing
concerns in Canada regarding excessive withdrawal south of the border
and in the U.S. regarding nitrate contamination originating north
of the border make this particular aquifer one of international interest.
While much emphasis in GIScience is on theoretical solutions to data
integration, such as current ontology research, this study addresses
pragmatic ways of integrating data across borders. Numerous interoperability
challenges including the availability of data, metadata, data formats
and quality, database structure, semantics, policies, and cooperation
are identified as inhibitors of data integration for cross-border
studies. The final section of the paper outlines two possible solutions
for standardizing classification schemes for ground-water models
- once data heterogeneity has been addressed.
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