Speaker
Description
Modern sensors and analytical methods produce data at higher spatial and temporal resolution while adding new variables, data types, and processing steps. This is particularly evident in geosciences, where information from different locations, instruments, sampling campaigns, and analytical workflows needs to be considered together. The central challenge is therefore no longer a lack of data, but our ability to structure this complexity so that humans can efficiently explore multidimensional relationships.
Users must be able to find relevant information, select suitable subsets, understand the context of measurements, and recognize relationships among variables and data products. Complex datasets may remain underused when these tasks require substantial time or technical expertise.
A strategy for addressing this challenge is the use of Multiple Coordinated Views (MCV). An MCV interface combines several linked visual representations of the same dataset. Selecting or filtering data in one view updates the corresponding information in the others, allowing users to examine data from different perspectives while retaining their spatial and scientific context.
We implemented such an interface on top of a structured environmental database and demonstrate its application using a case study from the Wadden Sea. The interface links spatial information, sedimentological measurements, scientific analyses, and underlying processing workflows. Users can move from spatial patterns to individual samples, compare variables across representations, filter views simultaneously, and trace analytical results back to their source data and methods. We show how these functions reduce the need to manually combine separate files and software tools and make relationships among locations, observations, variables, and analytical results more accessible. The MCV approach thereby supports both scientific interpretation and the practical reuse of complex environmental data.