This is the unspecified version of the paper.This version of the publication may differ from the final published version. Abstract-Cohort studies in medicine are conducted to enable the study of medical hypotheses in large samples. Often, a large amount of heterogeneous data is acquired from many subjects. The analysis is usually hypothesis-driven, i.e., a specific subset of such data is studied to confirm or reject specific hypotheses. In this paper, we demonstrate how we enable the interactive visual exploration and analysis of such data, helping with the generation of new hypotheses and contributing to the process of validating them. We propose a data-cube based model which handles partially overlapping data subsets during the interactive visualization. This model enables seamless integration of the heterogeneous data, as well as linking spatial and non-spatial views on these data. We implemented this model in an application prototype, and used it to analyze data acquired in the context of a cohort study on cognitive aging. We present case-study analyses of selected aspects of brain connectivity by using the prototype implementation of the presented model, to demonstrate its potential and flexibility. . Permanent repository link

Flows through tubular structures are common in many fields, including blood flow in medicine and tubular fluid flows in engineering. The analysis of such flows is often done with a strong reference to the main flow direction along the tubular boundary. In this paper we present an approach for straightening the visualization of tubular flow. By aligning the main reference direction of the flow, i.e., the center line of the bounding tubular structure, with one axis of the screen, we are able to natively juxtapose (1.) different visualizations of the same flow, either utilizing different flow visualization techniques, or by varying parameters of a chosen approach such as the choice of seeding locations for integration-based flow visualization, (2.) the different time steps of a time-dependent flow, (3.) different projections around the center line , and (4.) quantitative flow visualizations in immediate spatial relation to the more qualitative classical flow visualization. We describe how to utilize this approach for an informative interactive visual analysis. We demonstrate the potential of our approach by visualizing two datasets from two different fields: an arterial blood flow measurement and a tubular gas flow simulation from the automotive industry.

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Comparing time surfaces at different integration time points, or from different seeding areas, can provide valuable insight into transport phenomena of fluid flows. Such a comparative study is challenging due to the often convoluted shapes of these surfaces. We propose a new approach for comparative flow visualization based on time surfaces, which exploits the idea of embedding the surfaces in a carefully designed, reformed 2D visualization space. Such an embedding enables new opportunities for comparative flow visualization. We present three different strategies for comparative flow visualization that take advantage of the reformation. By reforming the time surfaces, we not only mitigate occlusion issues, but we can devote also the third dimension of the visualization space to the comparative aspects of the visualization. Our approach is effective in a variety of flow study cases. The direct comparison of individual time surfaces reveals small scale differences and fine details about the fluid's motion. The concurrent study of multiple surface families enables the identification and the comparison of the most prominent motion patterns. This work was developed in close collaboration with an expert in fluid dynamics, who assessed the potential usefulness of this approach in his field.