Multivariate Visualization of Data Quality Elements for Coastal Zone Monitoring

Broad sandy beaches and extensive dune ridges dominate the Dutch coastal zone. The beach areas are subject to continuous processes as beach erosion and sedimentation, which influence its morphology. This in turn has an economic impact on beach management and public security. Beach nourishments are carried out if safety of the land is at risk. Here the problems are defined as: (1) how to localize and quantify beach areas that require nourishment, and (2) how to assist the decision maker to manage the process of nourishment in time. To tackle the above-mentioned problems we used geographic information of different sources. We introduced an ontology-driven approach to integrate the different data sources and to conceptualize the beach areas, their attributes and relationships. An ontological approach greatly helps to understand the role of the quality of the data sources and also the required qualities for the decision maker. To express the data quality derived from metadata as well as from user-required qualities, we presented a novel visual environment for illustrating quantitative values of quality elements using multivariate visualization techniques. Quality elements that we studied for the beach nourishment process are: positional accuracy, thematic accuracy, temporal accuracy and completeness. By combining multivariate visualization with the technique of multiple linked views different aspects of data quality can be conveyed in relation to the original data. We conclude that the prototype can be useful for interactive and explorative purposes and has its strengths to deal with non temporal, as well as multi-temporal data.