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.
All these application domains are confronted with a rapidly growing number of data dimensions. Examples include smart-grid data in the energy context and an explosion of sensors in manufacturing. This often means a disruptive change to previous analysis methods and limits the applicability of existing standard tools for monitoring and analysis.
For such high-dimensional data, the project En2VA designs and develops new Visual Analytics methodologies for multiple important benefits:
- Save time of domain experts and data scientists for data preparation by novel interactive approaches to data editing.
- Build more accurate and understandable predictive models with higher confidence (e.g., regression models and decision trees) by novel visual approaches for model selection and validation.
- Increase the confidence of decision makers based on new methods for automatically generating intelligent reports.
- En2VA will also address scalability issues for creating effective overviews of high-dimensional data such as thousands of measured quantities as well as enable a progressive analysis of up to billions of data records.
In close collaboration with the company partners Austrian Power Grid, AVL List, HAKOM Solutions, Plasmo, and RHI, En2VA conducts a research approach with a strong focus on solving real-world problems of real users on real data. Specifically, all research results of En2VA are delivered as operational dashboards based on the software platform Visplore.