Towards combining attribute-based and time series-based visual querying

We present a concept for the visual-interactive definition of meaningful subsets in data sets comprising multivariate attributes and time series data. Based on a generalization of requirements of a real-world user group, we propose a three-stage approach, combining visual-interactive querying, query filter analysis, and result exploration. The approach includes several design parameters that can easily be adapted in future design studies for alternative applications.