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Hans-Jörg Schulz

Model-Driven Design for the Visual Analysis of Heterogeneous Data

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DOI

As heterogeneous data from different sources is being increasingly linked, it becomes difficult for users to understand how the data is connected, to identify what means are suitable to analyze a given data set, or to find out how to proceed for a given analysis task. We target this challenge with a new model-driven design process that effectively co-designs aspects of data, view, analytics and tasks. We achieve this by using the workflow of the analysis task as a trajectory through data, interactive views and analytical processes. The benefits for the analysis session go well beyond the pure selection of appropriate data sets and range from providing orientation or even guidance along a preferred analysis path to a potential overall speed-up, allowing data to be fetched ahead of time. We illustrate the design process for a biomedical use case that aims at determining a treatment plan for cancer patients from the visual analysis of a large, heterogeneous clinical data pool. As an example for how to apply the comprehensive design approach, we present Stackʼn'flip, a sample implementation which tightly integrates visualizations of the actual data with a map of available data sets, views and tasks, thus capturing and communicating the analytical workflow through the required data sets.
Original languageEnglish
JournalIEEE Transactions on Visualization and Computer Graphics
Volume18
Issue6
Pages (from-to)998-1010
Number of pages13
ISSN1077-2626
DOIs
Publication statusPublished - 2012

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