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
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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.