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NOTICE: This version of the NSF Unidata web site (archive.unidata.ucar.edu) is no longer being updated.
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To learn about what's going on, see About the Archive Site.
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Everything is a feature..... Hi Ben:So I actually got a little time to think, and I never was very fast and as an old fogey my brain is getting even slower, but....In an abstract sense, it may make sense that everything is a feature, but in a practical sense it will lead to a tools/data mismatch that is not efficient, and therefore I do not feel is a useful model.For example, in statistics the tools that you use if the data are iid are different than the tool you use if the data are a time series, and are different than the tools you use if the data is purely spatial, and these differ than from the tools for space- time, and multivariate timeseries, and multivariate space-time data. There is no one method works best under all situations. If all I know is that I am getting back is a feature, I know very little, and matching the feature to the tool will be difficult.Same with visualization tools - some are best for certain types of data, and no one is best for all types (GIS systems are crummy with dealing with time, or time/depth). Having data models that reflect the types of data that we have (or the types of data that will be returned) allows for the proper match.
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