Integrated Storage and Querying of Spatially Varying Data Quality Information in a Relational Spatial Database

Abstract

AbstractThis article investigates a new, integrated technique for storing and retrieving spatially varying data quality information in a relational spatial database. Rather than storing global data quality statements, the system enables data quality information to be referenced to a spatial framework, individual spatial objects, or even parts of spatial objects. The integrated model, called as RDBMS for Spatial Variation in Quality (RSVQ), allows flexible storage of spatially varying data quality information, and seamless querying irrespective of the underlying storage model. RSVQ is founded on a formal model of relational databases, defining a new derived, polymorphic query operator to join quality data with spatial data. The operator is implemented in an extension to SQL as a new WITHQUALITY keyword. A performance evaluation of RSVQ was conducted, using an Oracle Spatial database and a case study of cadastral data for parts of Victoria, Australia. The results of this evaluation demonstrated that the system is practical and efficient for a wide range of queries, as well as indicating the performance trade‐offs associated with the different data quality storage models. Using the integrated RSVQ approach provides the potential for a single, consistent, database engine for a wide range of existing and proposed spatial data quality management systems.