The cause of irritable bowel syndrome (IBS), a chronic disorder characterized by abdominal pain and disturbed bowel habits, is largely unknown. It is believed to be related to physical properties in the gut, central mechanisms in the brain, psychological factors, or a combination of these. To understand the relationships within the gut-brain axis with respect to IBS, large numbers of measurements ranging from stool samples to functional magnetic resonance imaging are collected from patients with IBS and healthy controls. As such, IBS is a typical example in medical research where research turns into a big data analysis challenge. In this chapter we demonstrate the power of interactive visual data analysis and exploration to generate an environment for scientific reasoning and hypothesis formulation for data from multiple sources with different character. Three case studies are presented to show the utility of the presented work.

We present a method for interactive global illumination of both static and time-varying volumetric data based on reduction of the overhead associated with re-computation of photon maps. Our method uses the identification of photon traces invariant to changes of visual parameters such as the transfer function (TF), or data changes between time-steps in a 4D volume. This lets us operate on a variant subset of the entire photon distribution. The amount of computation required in the two stages of the photon mapping process, namely tracing and gathering, can thus be reduced to the subset that are affected by a data or visual parameter change. We rely on two different types of information from the original data to identify the regions that have changed. A low resolution uniform grid containing the minimum and maximum data values of the original data is derived for each time step. Similarly, for two consecutive time-steps, a low resolution grid containing the difference between the overlapping data is used. We show that this compact metadata can be combined with the transfer function to identify the regions that have changed. Each photon traverses the low-resolution grid to identify if it can be directly transferred to the next photon distribution state or if it needs to be recomputed. An efficient representation of the photon distribution is presented leading to an order of magnitude improved performance of the raycasting step. The utility of the method is demonstrated in several examples that show visual fidelity, as well as performance. The examples show that visual quality can be retained when the fraction of retraced photons is as low as 40%-50%.

In this work we present a volume exploration method designed to be used by novice users and visitors to science centers and museums. The volumetric digitalization of artifacts in museums is of rapidly increasing interest as enhanced user experience through interactive data visualization can be achieved. This is, however, a challenging task since the vast majority of visitors are not familiar with the concepts commonly used in data exploration, such as mapping of visual properties from values in the data domain using transfer functions. Interacting in the data domain is an effective way to filter away undesired information but it is difficult to predict where the values lie in the spatial domain. In this work we make extensive use of dynamic previews instantly generated as the user explores the data domain. The previews allow the user to predict what effect changes in the data domain will have on the rendered image without being aware that visual parameters are set in the data domain. Each preview represents a subrange of the data domain where overview and details are given on demand through zooming and panning. The method has been designed with touch interfaces as the target platform for interaction. We provide a qualitative evaluation performed with visitors to a science center to show the utility of the approach.

Interactive volume rendering in its standard formulation has become an increasingly important tool in many application domains. In recent years several advanced volumetric illumination techniques to be used in interactive scenarios have been proposed. These techniques claim to have perceptual benefits as well as being capable of producing more realistic volume rendered images. Naturally, they cover a wide spectrum of illumination effects, including varying shading and scattering effects. In this survey, we review and classify the existing techniques for advanced volumetric illumination. The classification will be conducted based on their technical realization, their performance behaviour as well as their perceptual capabilities. Based on the limitations revealed in this review, we will define future challenges in the area of interactive advanced volumetric illumination.

In visualization, the combined role of data reconstruction and its classification plays a crucial role. In this paper we propose a novel approach that improves classification of different materials and their boundaries by combining information from the classifiers at the reconstruction stage. Our approach estimates the targeted materials’ local support before performing multiple material-specific reconstructions that prevent much of the misclassification traditionally associated with transitional regions and transfer function (TF) design. With respect to previously published methods our approach offers a number of improvements and advantages. For one, it does not rely on TFs acting on derivative expressions, therefore it is less sensitive to noisy data and the classification of a single material does not depend on specialized TF widgets or specifying regions in a multidimensional TF. Additionally, improved classification is attained without increasing TF dimensionality, which promotes scalability to multivariate data. These aspects are also key in maintaining low interaction complexity. The results are simple-to-achieve visualizations that better comply with the user’s understanding of discrete features within the studied object.

Molecular visualization is often challenged with rendering of large molecular structures in real time. We introduce a novel approach that enables us to show even large protein complexes. Our method is based on the level-of-detail concept, where we exploit three different abstractions combined in one visualization. Firstly, molecular surface abstraction exploits three different surfaces, solvent-excluded surface (SES), Gaussian kernels and van der Waals spheres, combined as one surface by linear interpolation. Secondly, we introduce three shading abstraction levels and a method for creating seamless transitions between these representations. The SES representation with full shading and added contours stands in focus while on the other side a sphere representation of a cluster of atoms with constant shading and without contours provide the context. Thirdly, we propose a hierarchical abstraction based on a set of clusters formed on molecular atoms. All three abstraction models are driven by one importance function classifying the scene into the near-, mid- and far-field. Moreover, we introduce a methodology to render the entire molecule directly using the A-buffer technique, which further improves the performance. The rendering performance is evaluated on series of molecules of varying atom counts.

In this position paper we discuss the usage of various interaction technologies with focus on the presentations of 3D visualizations involving a presenter and an audience. While an interaction technique is commonly evaluated from a user perspective, we want to shift the focus from a sole analysis of the naturalness and the ease-of-use for the user, to focus on how expressive and understandable the interaction technique is when witnessed by the audience. The interaction process itself can be considered to be a communication channel and a more expressive interaction technique might make it easier for the audience to comprehend the presentation. Thus, while some natural interaction techniques for interactive visualization are easy to perform by the presenter, they may be less beneficial when interacting with the visualization in front of (and for) an audience. Our observations indicate that the suitability of an interaction technique as a communication channel is highly dependent on the setting in which the interaction takes place. Therefore, we analyze different presentation scenarios in an exemplary fashion and discuss how beneficial and comprehensive the involved techniques are for the audience. We argue that interaction techniques complement the visualization in an interactive presentation scenario as they also serve as an important communication channel, and should therefore also be observed from an audience perspective rather than exclusively a user perspective.