Culture Classification

In order to describe physical objects in the world ("Culture"), we need to be able to say what kind of object it is.  This process of grouping things into categories is called an ontology. [definition: An ontology is a specification of a conceptualization.]

This page contains a rough classification of "Culture" objects, with an emphasis on the practical use of organizing a set of visual models, representative of the entire spectrum of objects made by humans.

Put another way, the goal is to come up with a complete list of terms which give useful information about the visual appearance of a man-made object on the terrain.

  1. Guiding principles

  2. Open Issues

  3. The Classification (Evolving draft)

  4. References

  5. Overview of Classification Challenges by Michael Flaxman


Guiding principles

Open Issues

The Classification (Evolving draft)

References

The following have been consulted for items to incorporate into the classification.

A huge reference that has not been incorporated is the UK Ordnance Survey (OS) MasterMap real-world object catalog (12 MB PDF).  It includes a vast number of feature classifications, many of which correspond to our definition of culture - primarily those described as of type "TopographicPoint".  However, a quick glance that shows that many or most of their classifications are based on abstract rather than physical representation, e.g. "Boundary Post/Stone/Tablet" which is based on the objects use (as a boundary marker) rather than its form.

Overview of Classification Challenges by Michael Flaxman:

How to best allow broad, top-down control without getting into the complexities of a full AI-like system?

As an end point, we have "visual representations" with at least the following important properties: some instances are selected, from a pool of candidates meeting all requirements these instances are placed, either at a specific geographic location, or relative to other resources each instance has certain properties which are fixed within a particular representation, and some which are variable of the variable properties, some are defaulted and some are data - driven of those which are data-driven, some are specified exactly and some are probabilistic

At the starting point, we have the real world (or some past or alternative future), which has a multitude of objects, and many disciplines devoted to cataloging and explaining these objects in various sometimes overlapping, sometimes conflicting classification systems. We would like to make use of the expert's classifications to drive some of the properties of our visual representation, without having to resolve conflicts in any elaborate way.

Perhaps the simplest means of doing this is to allow only a single classification, which controls all visual properties within its domain. Restricting architects and urban planners to a single typology of buildings - this is generally what most GIS systems do, mapping attributes to colors or symbols.

A more complex, but still controllable, setup might be to allow multiple classifications, but each uniquely mapping to a single visual simulation attribute. So, a zoning map could drive buildings by use, while a separate real estate value model could be mapped to building height, for example. If the real estate value model would predict a taller building than allowed by zoning, that discrepancy would be up to the user to catch.

This same kind of mapping system would work somewhat less well for vegetation, since the interactions become more significant.