Research topics

Reference projects, applications and publications

Screenshot of the Brain* software of the VRVis showing a gray brain with many colored neuronal networks.
The VRVis data science platforms not only make it easy to handle extremely large heterogeneous data, as is the case in life sciences and medicine, but also enable better data and data network comprehensibility through integrated visualization.

Data Science for Medicine and Life Science

Data Science plays an increasing role in the fields of medicine and life sciences. VRVis has already successfully implemented several data science projects in the areas of neuroscience and medicine for the analysis of health and patient cohort data. Furthermore, VRVis has developed Brain*, a globally used platform for the integration, management and exploration of spatial brain data.

Three people are standing in front of a laptop in a factory environment.
Data analysis tools optimized visually and graphically for human perception are the decisive key element that strengthens users' confidence in computer-aided data science and decision-making processes.

Visual Analytics for Industry 4.0

As a key technology in the field of industrial production, visual analytics enables us to see through the data surrounding the production process through visual data analysis. In this context, the stability and scalability of visual analytics tools are crucial factors for their acceptance as reliable tools in Industry 4.0, such as in our INGRESS project. Our analytics solutions are characterized by their ability to handle complex data, as well as to perform pattern search and anomaly detection quickly and reliably.

Bild einer Fischwanderhilfe und eines Staudamms mit Landschaft
The energy sector benefits significantly from intelligent visual data science solutions that contribute to the sustainable use and maintenance of hydropower plants, for example.

Digitalization and Predictive Maintenance in Hydropower

Hydropower is an important part of Austrian renewable energy. However, many hydropower plants are older structures. In our DIGI-Hydro project, a hydropower plant is retrofitted with new measurement sensors and advanced data analytics to facilitate real-time monitoring and better maintenance with the help of a digital (hydropower) twin.