Visualizations support the comprehensibility of data in all sectors. The goal is not only to produce images from data, but above all to provide new insights into this data. We focus our research on new interactive visualization methods that support experts from different fields in the exploration, analysis and presentation of complex data. In doing so, we focus on those problems that cannot be solved with purely automatic methods.
The data types we mainly work with are spatial 3D data derived from simulations or image acquisition techniques, large geographic data, abstract data and spatio-temporal data from tracking techniques.
In our research work we have successfully solved many problems related to the understanding of time series data, animal or human trajectories, flow data, GIS data, infrastructure data and much more. In particular, we focus on: quantitative visual analysis, visualization for heterogeneous simulation data and large-scale geovisualization.
In the field of quantitative visualization we are working on making purely qualitative analyses quantifiable through special extensions for existing visualization programs and concepts. In this way, we are responding to the needs of many areas, such as medical diagnostics, automotive simulations or general decision-making processes for which the analysis results must be made comprehensible and reproducible.
For the visualization of heterogeneous data, such as those frequently encountered in medicine or simulations, we create systems that reconcile, register and analyze data from different sources and in a wide range of resolutions. We also develop complex data models and corresponding analysis techniques that enable the analysis of large collections of time series or surface data.
For the visualization of enormous amounts of data, as they occur with geodata from large terrain models or 3D data from time-dependent simulations, we have developed interactive large-scale 3D visualizations, which are particularly suitable for use in complex infrastructure projects: The possibility of combining data sets from various planning disciplines in one system, as well as showing further simulation results in their actual context, makes planning projects and information understandable for experts as well as laymen.
In our first systematic audience study, "A Comparison of Radial and Linear Charts for Visualizing Daily Patterns", published in IEEE Transactions on Visualization and Computer Graphics and presented at IEEE VIS, we investigated the advantages and disadvantages of radial charts for visualizing periodic time-dependent data. Since there has been no systematic discussion of radial representation of periodic day patterns in the scientific literature, our research results were able to define visualization guidelines for the first time.
There are numerous scientific examples where the movement and behaviour patterns of people, animals or even vehicles are recorded. Together with the spatial and temporal context, the resulting trajectories represent a complex, heterogeneous set of data. In order to be able to present these data in interactive visualizations in a meaningful way, a hybrid approach combining automatic and interactive analyses is often required: Our innovative interactive visualization tools, combined with machine learning and deep learning techniques, enable efficient analysis in this case. Our expertise includes behavioural research in a number of contexts, for example in the context of T-Maze experiments.
GEARViewer is the result of many years of research on the visualization of complex infrastructure projects and is based on our high-performance visualization framework Aardvark. The tool, developed together with project partner Geoconsult Wien ZT GmbH, allows the interactive exploration of extensive geographical areas as well as the analysis, simulation and presentation of the effects of large-scale infrastructure buildings on urban and rural environments. For example, a dynamic information and guidance system on the main access roads to Munich Airport was planned and tested using GEARViewer.
The aim of the project IVC Stream is to research novel visual computing solutions for simulation and measurement data.
The strategic project of the area is the organizational and scientific hub for the realization of the area-wide intelligent visual computing approach for analytics and modelling based on ensembles of dense grid-based data, derived data, and digital embedding.
The research goal of AMASE is to create a suite of tools and methods to ingest, process, visualize, and manipulate heterogeneous, large-scale geospatial data. This data is the constantly updated representation of the real world in the form of an evolving digital twin.
The main goal of this project is to enable a reliable decision support for large-scale infrastructure projects by providing solutions for a collaborative visual analysis of digital twins.
The main objective of the strategic project ARCS is the design of software architectures that enable interactive visualization systems to ingest large volumes and velocities of geospatial and associated non-geometric data.
The goal of the project MARAMT is to develop a software framework to significantly reduce the effort required to work with existing and future complex cyber-physical systems.
Within the project Larvalbrain 2.0, a dynamic multi-scale multi-level atlas and data collection of structural, molecular, physiological, and behavioral results of Drosophila melanogaster larvae will be established.
Visdom's hydrodynamic simulations provide precise water level predictions at any point on a water surface in the "PegelAlarm" app.
To take full advantage of data from automotive simulations and measurements, we combine interactive and automatic Visual Computing methods to find intuitive, efficient and effective solutions that are applicable in the daily routine of engineers.
MINERVA is an integrated framework for planetary scientists allowing members of different instrument teams to cooperate synergistically in virtual workspaces by sharing observations, analyses and annotations of heterogonous mission data.
ARCHES - Accessible Resources for Cultural Heritage EcoSystems was an EU-funded Horizon2020 project coordinated by VRVis.
The long-term vision of this applied research project is to use available data resources to improve image-based diagnostics based on complex data in daily clinical routine.
The combination of "liquid biopsies", machine learning and data visualization aims to enable earlier and more accurate prediction of a relapse in children with cancer.
Visual Analysis of Asteroid Deflection.
For many years we have been dealing with all aspects of hydrodynamic modelling. With our software Visdom we can model different scenarios and also offer this as a service.
New technologies and security policy developments bring a paradigm shift for the Austrian armed forces. The use of information and communication measures entails both challenges and opportunities: for combat, security and rescue manoeuvres.
We create a digital twin of a community and simulate weather events to identify high-risk buildings and infrastructure vulnerabilities.
In this project tools and methods for handling, administration, manipulation and evaluation of several different data sources for measurements and lighting design are developed.
The strategic project forms the organizational and scientific hub for the realization of an area wide integrative visual computing approach. It covers joint strategic research and development on fundamental challenges in all application projects.
The HORA 3 project focuses on flood modelling for all rivers and streams in Austria. The results are detailed flood risk maps for different annual periods.
Hands-on flood management with the Visdom decision software, which simulates and visualizes flood and heavy rain events.
Understanding how the brain works is one of the biggest challenges addressed by neuroscientists today. Modern neuroscience research is extremely data-intensive and requires special software infrastructures to enable and accelerate the discovery of the complex interplay of genes, structure and function.
Research project on powerful visualization methods to support decision making in complex infrastructure projects, especially in tunnel, railway and road construction.
Visualization and visual analysis of high-resolution surface reconstructions find a wide range of applications, from tunnel monitoring and archaeological excavations to the change management of cultural heritage buildings.
Digital representations of the real world and digital twins are becoming increasingly important for planning, situation assessment and decision-making.
Support for planetary research: Visual analysis of reconstructions of the Mars surface and view planning for rover camera instruments.
Virtual exploration and geological analysis of reconstructed Mars surfaces and rock outcrops.
Complex simulation data is practically omnipresent today.
The goal of the applied research project En2VA (“Visual Analytics for Energy and Engineering Applications”) is to increase the efficiency and the quality of advanced analytics for high-dimensional data from manufacturing, engineering, and the energy sector.
Visual computing for medicine: image processing solutions for new applications in radiology.
Barrier-free access to art and museums for blind and visually impaired people through 3D technology.
With Augmented Reality, simulation results of car engine noises become visible.
For centuries, neuroscientists have been mapping the brain. Until now, the step from simple maps to a generally accepted model has proved to be extremely difficult. In this project, a 4D atlas of the brain of the fruit fly larva is being built.
A visual tool for a combined stratigraphic and temporal documentation and interpretation of excavation projects.
Novel visual analysis technologies for high-dimensional data in automotive engineering, industrial manufacturing and the energy sector
A more efficient way to create operating manuals from existing databases for product life cycle management using Augmented Reality.
Decision support system for floods and inundations for the trading district of Shenzen, China.
With the KAUST Scene Generator three-dimensional road networks can be generated from open-source OpenStreetMap data.
Strategic Research in Scalable, Semantic Rendering.
Localization of Virtual Sound Sources: Effects of Pointing Method, Visual Environment, and Training.
Flood protection through simulation and visualization: Reducing the effects of floods and communicating measures to the public.
Planetary Robotics Vision Data Exploitation.
Investigation of techniques enabling a seamless analysis of data from multi-run simulations on multiple degrees of detail.
Seamless visual analysis of data involving 3D geometry, relational information and multivariate attributes.
Research and development of novel interactive visualization methods for visualization and understanding of complex systems.
In order to preserve the architectural heritage, we use methods of photogrammetry, thermography, photometry as well as laser scans to carry out inventories, recognition and documentation of changes in protected buildings.
Algorithms to improve the visual analysis of surface reconstructions.
VRVis contributes data analytics and visualization tools tailored to support and accelerate research of the Haubensak Group at the Institute of Molecular Pathology Vienna.
High-quality lighting simulation requires dynamic, interactive, realistic real-time lighting simulation for various complex architectural environments.
Visual computing techniques for the automated detection of osteoporosis and osteoarthritis.
Software for the use of multi-modality images in external radiotherapy.
Visual Analytics for Modeling and Simulation: Improvement of simulation setup and design scenarios with tools and methods of Visual Analytics.
Improving and combining multiple sensors to increase the accuracy and reliability of modern surveying equipment.
Decision support systems and 3D viewing technologies for tunnel construction.
Next generation workflows for interactive knowledge generation from images and simulations.
The analysis, visualization and exploration of high-dimensional image spaces are the subject of the KAFus project.