The focus of the group is on multi- and high-dimensional data which is in many cases time-dependent. The group’s goal is to help users acquire new insights and increased decision confidence by enabling an interactive dialogue with big structured data. For this purpose, the researchers of the Visual Analytics group create novel technologies which combine visualization, user interaction, and automatized analysis methods such as data mining with response in real-time. The application domains of current projects comprise, e.g., the energy sector, industrial manufacturing, health policymaking, and simulation-based development of powertrain systems.
The research of our Visual Analytics group focuses on creating effective visual techniques for supporting tasks along the process of data analysis:
An additional research topic concerns the creation of highly responsive software infrastructures which provide immediate feedback on user interaction even in case of large data. In this context, the research group focusses on tightly integrating popular analytical platforms such as Matlab, R, and Python, as well as on defining flexible modules which permit rapid prototyping of task-specific analytical applications.
Head of Visual Analytics, Visual Analytics
johanna.schmidt(at)vrvis.at +43 1 908 98 92 302Behind our smart solutions and software are smart and driven people. Do you want to meet the team?
Information Visualization
Visual Analytics
Machine Learning
Analytical software architectures
Human-computer interaction
Data science for conducting specific data analyses
Visplore is a software platform permitting rapid and flexible creation of task-specific analytical applications interactively by the user. Visplore has been designed for the visual exploration of multi- to high-dimensional data, including categorical and functional data. The focus is on supporting specific tasks such as data quality assessment, process optimization, and the analysis of prediction models. The software architecture exploits parallelism in order to support interactive analysis of millions of data records in real-time. Visplore has served as a software platform for numerous scientific results of the Visual Analytics group, as well as for applications, e.g., in the automotive industry, the energy sector, industrial manufacturing, the health sector, and for network security. More about Visplore.
Partners: Austrian Power Grid AG, HAKOM Solutions GmbH
Quality assessment of time series data; validation and comparison of predictive models
Partners: AVL List GmbH
Validation of simulation data, sensitivity analysis, multi-objective optimization
Partners: RHI AG, Plasmo Industrietechnik GmbH
Monitoring of production processes and production fault; analysis for process optimization
Partners: Hauptverband österreichischer Sozialversicherungsträger, Gesundheit Österreich GmbH
Quality assessment of accounting data, monitoring and analysis of health system performance indicators
Partners: Schedule Coordination Austria GmbH, AI-MS Aviation Infrastructure Management Systems GmbH
Identification of correlations and trends, data preparation, detail analysis of flight schedule optimization results
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.
Businesses go smart with Data Science: with the help of visual data analysis, machine learning, deep learning, data mining and visual data processing we help companies to fully exploit the potential of their data.
In this project we develop new methods from the field of visual analysis and machine learning to automate the quality control and quality assurance of glass articles.
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.
Novel visual analysis technologies for high-dimensional data in automotive engineering, industrial manufacturing and the energy sector
DEXHELPP develops new methods to support analysis, planning and control in health care by combining decision analysis, data security, data management, statistics, mathematical modelling, simulation and visual analysis.