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The feature type defines the spatial data support for features of its type, i.e. if you can store spatial data for this feature or not, and if spatial data is stored once for the feature or (xor) separately for each observation of a feature.

Table 1 summarizes the possible spatial data support types. The spatial data support is part of the feature type definition and can therefore not be changed by the user.

Spatial data  support

Notes

No spatial data support

Used for feature types that have no relation to some real world location.

An Example would be a feature type called Monthly income of employee, where the observations would record the monthly income. In this case neither the feature nor its observations would have any relation to a real world location.

Spatial data for feature (SSF)

Storing spatial data for the feature and storing the feature's observations without spatial data is common for most feature types since it represents the typical scenario when observations are collected over time for a non-moving feature.

An example could be a feature type called Surface temperature, where the observations would represent the surface temperature of a a specific location over time. While the feature itself will have a location, this location will not move over time.

Spatial data for observations (SSO)

Storing spatial data with each observation is usually allowed by feature types where the feature may change its location with every observation. An example would be a feature type called bear sightings, where the feature is one specific bear and each observation records a sighting of a specific bear (e.g. in a national park).

If spatial data is stored for observations, the Application Server can derive spatial information for the feature. For that the Application Server uses either the first or the last observation, or an observation that is closest to a specific date&time.

Table 1: Spatial data support for feature types.

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