Tracking the temporal evolution of features in time-varying data is a key method in visualization. For typical feature definitions, such as vortices, objects are sparsely distributed over the data domain. In this paper, we present a novel approach for tracking both sparse and space-filling features. While the former comprise only a small fraction of the domain, the latter form a set of objects whose union covers the domain entirely while the individual objects are mutually disjunct. Our approach determines the assignment of features between two successive time-steps by solving two graph optimization problems. It first resolves one-to-one assignments of features by computing a maximum-weight, maximum-cardinality matching on a weighted bi-partite graph. Second, our algorithm detects events by creating a graph of potentially conflicting event explanations and finding a weighted, independent set in it. We demonstrate our method's effectiveness on synthetic and simulation data sets, the former of which enables quantitative evaluation because of the availability of ground-truth information. Here, our method performs on par or better than a well-established reference algorithm. In addition, manual visual inspection by our collaborators confirm the results' plausibility for simulation data.

Immersive visualization (IV) fosters the creation of mental images of a data set, a scene, a procedure, etc. We devise an initial version of a design space for categorizing workflows that take advantage of IV. From this categorization, specific requirements for an actual, seamless IV-integration can be derived. We validate the design space with three workflows investigated in our research projects.

Virtual Reality (VR) has been an active field of research for several decades, with 3D interaction and 3D User Interfaces (UIs) as important sub-disciplines. However, the development of 3D interaction techniques and in particular combining several of them to construct complex and usable 3D UIs remains challenging, especially in a VR context. In addition, there is currently only limited reusable software for implementing such techniques in comparison to traditional 2D UIs. To overcome this issue, we present ViSTA Widgets, a software framework for creating 3D UIs for immersive virtual environments. It extends the ViSTA VR framework by providing functionality to create multi-device, multi-focus-strategy interaction building blocks and means to easily combine them into complex 3D UIs. This is realized by introducing a device abstraction layer along sophisticated focus management and functionality to create novel 3D interaction techniques and 3D widgets. We present the framework and illustrate its effectiveness with code and application examples accompanied by performance evaluations.

Abstract Interactive analysis of 3D relational data is challenging. A common way of representing such data are node‐link diagrams as they support analysts in achieving a mental model of the data. However, naïve 3D depictions of complex graphs tend to be visually cluttered, even more than in a 2D layout. This makes graph exploration and data analysis less efficient. This problem can be addressed by edge bundling. We introduce a 3D cluster‐based edge bundling algorithm that is inspired by the force‐directed edge bundling (FDEB) algorithm [ HvW09b ] and fulfills the requirements to be embedded in an interactive framework for spatial data analysis. It is parallelized and scales with the size of the graph regarding the runtime. Furthermore, it maintains the edge's model and thus supports rendering the graph in different structural styles. We demonstrate this with a graph originating from a simulation of the function of a macaque brain.

To avoid simulator sickness and improve presence in immersive virtual environments (IVEs), high frame rates and low latency are required. In contrast, volume rendering applications typically strive for high visual quality that induces high computational load and, thus, leads to low frame rates. To evaluate this trade-off in IVEs, we conducted a controlled user study with 53 participants. Search and count tasks were performed in a CAVE with varying volume rendering conditions which are applied according to viewer position updates corresponding to head tracking. The results of our study indicate that participants preferred the rendering condition with continuous adjustment of the visual quality over an instantaneous adjustment which guaranteed for low latency and over no adjustment providing constant high visual quality but rather low frame rates. Within the continuous condition, the participants showed best task performance and felt less disturbed by effects of the visualization during movements. Our findings provide a good basis for further evaluations of how to accelerate volume rendering in IVEs according to user's preferences.

Data annotation finds increasing use in Virtual Reality applications with the goal to support the data analysis process, such as architectural reviews. In this context, a variety of different annotation systems for application to immersive virtual environments have been presented. While many interesting interaction designs for the data annotation workflow have emerged from them, important details and evaluations are often omitted. In particular, we observe that the process of handling metadata to interactively create and manage complex annotations is often not covered in detail. In this paper, we strive to improve this situation by focusing on the design of data annotation workflows and their evaluation. We propose a workflow design that facilitates the most important annotation operations, i.e., annotation creation, review, and modification. Our workflow design is easily extensible in terms of supported annotation and metadata types as well as interaction techniques, which makes it suitable for a variety of application scenarios. To evaluate it, we have conducted a user study in a CAVE-like virtual environment in which we compared our design to two alternatives in terms of a realistic annotation creation task. Our design obtained good results in terms of task performance and user experience.

Virtual Reality (VR) systems are of growing importance to aid decision support in the context of the digital factory, especially factory layout planning. While current solutions either focus on virtual walkthroughs or the visualization of more abstract information, a solution that provides both, does currently not exist. To close this gap, we present a holistic VR application, called Factory Layout Planning Assistant (flapAssist). It is meant to serve as a platform for planning the layout of factories, while also providing a wide range of analysis features. By being scalable from desktops to CAVEs and providing a link to a central integration platform, flapAssist integrates well in established factory planning workflows.

Metadata in- and output are important steps within the data annotation process. However, selecting techniques that effectively facilitate these steps is non-trivial, especially for applications that have to run on multiple virtual reality platforms. Not all techniques are applicable to or available on every system, requiring to adapt workflows on a per-system basis. Here, we describe a metadata handling system based on Android's Intent system that automatically adapts workflows and thereby makes manual adaption needless.

A key aspect of air traffic infrastructure projects is the communication between stakeholders during the approval process regarding their environmental impact. Yet, established means of communication have been found to be rather incomprehensible. In this paper we present an application that addresses these communication issues by enabling the exploration of airplane noise emissions in the vicinity of airports in a virtual environment (VE). The VE is composed of a model of the airport area and flight movement data. We combine a real-time 3D auralization approach with visualization techniques to allow for an intuitive access to noise emissions. Specifically designed interaction techniques help users to easily explore and compare air traffic scenarios.

Pie menus are a well-known technique for interacting with 2D environments and so far a large body of research documents their usage and optimizations. Yet, comparatively little research has been done on the usability of pie menus in immersive virtual environments (IVEs). In this paper we reduce this gap by presenting an implementation and evaluation of an extended hierarchical pie menu system for IVEs that can be operated with a six-degrees-of-freedom input device. Following an iterative development process, we first developed and evaluated a basic hierarchical pie menu system. To better understand how pie menus should be operated in IVEs, we tested this system in a pilot user study with 24 participants and focus on item selection. Regarding the results of the study, the system was tweaked and elements like check boxes, sliders, and color map editors were added to provide extended functionality. An expert review with five experts was performed with the extended pie menus being integrated into an existing VR application to identify potential design issues. Overall results indicated high performance and efficient design.

The analysis of time-dependent simulation data is a demanding task, both in terms of computing power and time. Interactive analysis using multiple linked views has been shown to be one possible solution to this problem. However, there are two significant short-comings when limited to a standard desktop-based setup: first, complex spatial relationships are hard to understand using only 2D projections of the data. Second, the size of today's simulation runs is too large to be handled even by powerful workstations. We describe a system for the interactive analysis of large, time-dependent data in virtual environments. Based on the techniques of multiple linked views and brushing, our approach allows the user to quickly formulate, visualize and assess hypotheses about the data. To enable an interactive exploration even in the face of multi-gigabyte data sets, we distribute the workload to a multi-processor parallel machine and a rendering client.

The application of virtual environments to scientific visualization provides the user with an intuitive interface to interact with the data to be analyzed. We present an approach that leverages the utilization of 3D interaction techniques to directly interact with scientific data. First, we propose an abstraction of VR-based interaction by decoupling the low-level interaction groundwork from high-level declarations of interaction behaviors. Second, we describe how recurring interaction patterns in scientific visualizations can be distilled into 3D widgets, exhibiting reusability for diverse participants in the development of interactive visualization. The benefits which follow from this approach are exchangeability of VR-toolkits and devices, faster development cycles and better code maintainability.

Abstract The analysis of unsteady phenomena is an important topic for scientific visualization. Several time‐dependent visualization techniques exist, as well as solutions for dealing with the enormous size of time‐varying data in interactive visualization. Many current visualization toolkits support displaying time‐varying data sets. However, for the interactive exploration of time‐varying data in scientific visualization, no common time model that describes the temporal properties which occur in the visualization process has been established. In this work, we propose a general time model which classifies the time frames of simulation phenomena and the connections between different time scales in the analysis process. This model is designed for intuitive interaction with time in visualization applications for the domain expert as well as for the developer of visualization tools. We demonstrate the benefits of our model by applying it to two use cases with different temporal properties.

Ventricular Assist Devices (VADs) support the heart in its vital task of maintaining circulation in the human body when the heart alone is not able to maintain a sufficient flow rate due to illness or degenerative diseases. However, the engineering of these devices is a highly demanding task. Advanced modeling methods and computer simulations allow the investigation of the fluid flow inside such a device and in particular of potential blood damage. In this paper we present a set of visualization methods which have been designed to specifically support the analysis of a tensor-based blood damage prediction model. This model is based on the tracing of particles through the VAD, for each of which the cumulative blood damage can be computed. The model's tensor output approximates a single blood cell's deformation in the flow field. The tensor and derived scalar data are subsequently visualized using techniques based on icons, particle visualization, and function plotting. All these techniques are accessible through a Virtual Reality-based user interface, which features not only stereoscopic rendering but also natural interaction with the complex three-dimensional data. To illustrate the effectiveness of these visualization methods, we present the results of an analysis session that was performed by domain experts for a specific data set for the MicroMed DeBakey VAD.

Nasal airway obstruction is a serious and common problem within the field of rhinology. This paper introduces VRhino II, a virtual-reality-based application for the analysis of the airflow through the human nasal cavity. This tool is currently developed within a research project striving to gain better insight into the flow conditions during respiration. The paper's focus lies on a general description of the application's design. Additionally, technical details about the main system components are given.

One recommended strategy for the analysis of CFD-data is the interactive exploration within virtual environments. Common visualization systems are unable to process large data sets while carrying out real-time interaction and visualization at the same time. The obvious idea is to decouple flow feature extraction from visualization. This paper covers the functionality of the parallel CFD post-processing toolkit Viracocha. Two aspects are discussed in more detail. The first approach covers strategies to reduce the loading time. Data caching and prefetching are employed to reduce access time. The second aspect concerns an approach called streaming that minimizes the time a user has to wait for first results. Viracocha already sends coarse intermediate data back to the virtual environment before the final result is available. Different streaming and data handling strategies are described. In order to emphasize the benefit of our implementation efforts, some strategies are applied to multi-block CFD data sets.