Storing and Querying Spatially Varying Data Quality Information Using an Integrated Spatial Rdbms

Current representations of spatial data quality (SDQ) do not adequately represent the spatial variation of SDQ. For example, a user who wants to know the positional accuracy of a feature usually has to rely on metadata statements, which usually refer to the entire data set. In reality, SDQ varies spatially; quality may be higher in some locations and lower in others perhaps due to different data collection and acquisition methods. To represent spatially varying data quality, SDQ may need to be stored for individual features and parts of features in a dataset. This paper proposes a new, flexible data model for efficient storage and retrieval of spatially varying quality information in a spatial database. The model can store quality information in different ways according to the requirements of the data set. SDQ can be stored alongside individual features or parts of features in the database, or as an independent spatial data layer. The paper reports on an extension to Oracle spatial RDBMS, used to implement this model of spatially varying SDQ. An investigation into the different querying mechanisms required to support this model of SDQ shows that the different model allows a flexible representation of spatially varying quality, including modeling sub-feature variation in quality.