Transforming Data into Knowledge
Acquisition | Structuring | Formalization | Visualization
Information and the knowledge derived from it have become two of the most important production factors in our economy. The research group breaks down information and expert knowledge into their basic building blocks so they can be integrated into a variety of computer applications.
Expert systems and self-learning, bio-inspired algorithms are used, inter alia, to make information quickly accessible and solution-oriented. The Knowledge Engineering group develops solutions in the fields of big data, high performance computing, data communication and visualisation of multivariate data.
The technologies used range from smart-phone apps to complex integrated online systems, to Hadoop, Spark and Python in the field of high performance computing.
Areas of application
- Collecting and analysing information, data and processes in interdisciplinary projects
- Processing, structuring and integrating large data and knowledge bases
- Implementing self-learning, fault-tolerant algorithms
- Usability concepts and designs
- Interactive communication and visualisation
- «Internet of Things» and Industry 4.0 applications
- High performance computing
Available from: https://doi.org/10.21256/zhaw-2777
Zbinden, Erich; Eggel, Thomas,
Available from: https://doi.org/10.21256/zhaw-2781
3D chemistry - platform and app for classroom use and teaching - digitalization
Three-dimensional imagination is highly relevant for understanding the fundamentals of chemistry at university level. Especially when drawing molecular structures, it is important that students are able to imagine molecules/salts with the right geometry, so that the correct functioning in environment/biology/chemistry can be deduced. So far, model ...
Mobile tool for the evaluation of forest edges - Digital Transformation
The tried and tested forest edge key (Krüsi et al. 2017) is suitable for recording the initial condition and later monitoring the success of forest edge enhancements, as it provides reproducible results and is easy to use (Fuhrer et al. submitted). For this reason, this forest edge key is to be further developed into a smartphone app. With the help ...