Towards spatial data quality information analysis tools for experts assessing the fitness for use of spatial data
Geospatial data users increasingly face the need to assess how datasets fit an intended use. However, information describing data quality is typically difficult to access and understand. Therefore, data quality is often neglected by users, leading to risks of misuse. Understanding data quality is a complex task that may involve thousands of partially related metadata. For complex cases where heterogeneous datasets have to be integrated, there is a need for tools supporting data quality analysis. This paper presents the design of such a tool that can manage heterogeneous data quality information and provide functions to support expert users in the assessment of the fitness for use of a given dataset. Combining concepts from GIS and Business Intelligence, this approach provides interactive, multi-granularity and context-sensitive spatial data quality indicators that help experts to build and justify their opinions. A prototype called the Multidimensional User Manual is presented to illustrate this approach.
spatial data quality fitness for use metadata indicators visualization spatial olap dashboard