Roger Bivand
Approaches to Classes for Spatial Data in R
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Access to well-structured and sometimes self-describing spatial position
data with associated data attributes in geographical scales domains
is increasing, and is expected to increase further. Until recently,
it has often been sufficient to treat data sets as autonomous, dropping
positional metadata attributes for analysis and visualization. It may be
argued that this is short-sighted, because positional data from different
sources may not then be readily co-registered. This contribution will
survey the representation of positional spatial data in contributed
packages to R, and suggest which alternatives exist, or might be
implemented, to provide underpinnings that, on the one hand, should make
it more convenient to ingest positional and attribute data for analysis,
and, on the other, to attempt to retain positional metadata so that the
results of analysis can also be utilized in other software contexts.