Multidimensional management of geospatial data quality information for its dynamic use within GIS

Abstract

Metadata should help users to assess the quality (fitness for use) of geospatial data, thus reducing the risk of data misuse. However, metadata presents limitations and remain largely unused. There still exists a need to provide information to users about data quality in a more meaningful way. This research aims to dynamically communicate quality information to the users in a rapid and intuitive way in order to reduce user meta-uncertainty related to geospatial data quality, and then reduce the risks of data misuses. Such a solution requires a data model able to support heterogeneous data quality information at different levels of analysis. Using a multidimensional database approach, this paper proposes a conceptual framework named the Quality Information Management Model (QIMM) relying on quality dimensions and measures. This allows a user to easily and rapidly navigate into the quality information using a Spatial On-Line Analytical Processing (SOLAP) client-tied to its GIS application. QIMM potential is illustrated by examples, and then a prototype and ways to communicate data quality to users are explored.