Bolded terms should end up in the ontology at least conceptually, albeit possibly with revised terms (at which point, the concept glossary should be changed to reflect this.)

def: Product Quality is a measure of how well we believe a dataset represents the physical quantity that it purports to. As such, it is closely related to (though not identical to) the level of validation of the dataset. It often varies within the dataset, with dependencies on such factors as viewing geometry, surface type (land, ocean, desert, etc.) and cloud fraction. cf.

def: Completeness is a product quality measure that describes how much of the space/time continuum is represented in the data. It may also reflect the spread of observing conditions under which the measurement is retrieved.

def: Spatial completeness describes how much of the globe is covered by a dataset. This is typically expressed as a percentage of the total globe. Alternatively, it may be qualified by the surface type, such as 90% of land surface.

def: Temporal completeness describes how much of the time continuum is covered by a dataset at a specific geographic location. This consists of (at least) two aspects: the total time range covered, and the revisit time, i.e., how frequently a satellite views a given point on the earth. An additional aspect is the local revisit time (better term?), i.e., how many different times of day are typically represented over a long period. Sun-synchronous data will have local revisit time coverage that is limited at the equator (i.e., the same time of day), but higher revisit time coverage at high latitudes where orbits overlap.

def: Observing-condition completeness describes under what viewing conditions, such as viewing geometry or cloud fraction, the measurement can be reliably retrieved. For example, AIRS can retrieve parameters in up to ~70% cloud fraction. Note however that this is usually not a hard cut off, but rather a deterioration of yield with increasing cloud fraction.

def: Consistency describes how reproducible a measurement is over long time periods, over spatial discontinuities (such as surface changes) and across different observing conditions, such as viewing geometry or cloud fraction.

def: Temporal Consistency describes whether the data exhibit variations in retrieved measurements over time that are not likely to reflect actual variations in the physical parameter being retrieved. Common forms of these include trends, discontinuities and anomalies.

def: Spatial Consistency describes how smoothly the measurement varies over significant spatial discontinuities where those discontinuities are not expected to give rise to data discontinuities.

def: Observing-condititon Consistency describes whether the data exhibit variations in retrieved measurements due to the viewing conditions, such as viewing geometry or cloud fraction.