Approaches to Classes for Spatial Data in R

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.