Concept

“Research needs creativity, spontaneity, impulses and expert feedback. With the Computational Science Hub, we will create an environment where researchers from all kinds of scientific areas that work with similar methods can come together, work on joint projects and inspire each other.” (Robert Jung, Spokesman of the CSH in an interview with the Hohenheimer Online Kurier on January 30, 2018)

The CSH is a platform where scientists from all three faculties (agricultural sciences, natural sciences, business, economics and social sciences), whose research involves processing and analysis of large data sets, modelling and simulation of complex systems, development of mathematical and statistical methods for data analysis or computational biology, can exchange their knowledge and expertise in the context of research and teaching. The aim is to strengthen the connections among scientists across faculties and, particularly, to combine domain knowledge from various disciplines with profound methodological expertise from “computational science” in order to promote innovative and transdisciplinary research and teaching at the University of Hohenheim.

In line with this idea, it is planned to locate parts of the participating institutes and departments - today spread over the campus - in one building in Steckfeldstr. 2. By bundling of competences and expertise in the development and application of data-intensive methods in one single place, the CSH will help create research impulses as well as new, state-of-the-art teaching concepts.

In this respect, the CSH actively contributes to the university-wide research topic “digital transformation”.

The scientists involved with the CSH initiative have domain knowledge in the fields: 

• Financial and commodity markets,
• innovation and sustainability,
• crop science and biology,
• digital agricultural science and diffusion processes,

as well as diverse and complementary methodological expertise in:

• Agent-based modeling (ABM),
• digital twinning,
• Microeconometrics (particularly quantitative evaluation methods for evidence based decision making),
• network analysis,
• quantitative text analysis and text mining,
• Statistical learning,
• design of experiments, and
• time series econometrics.

• Organisation of joint seminars and lectures on computational science.
• Development and implementation of inter-faculty courses and seminars for students and researchers in the following areas:
  - automated, computer-aided methods for data collection,
  - statistical and econometric data analysis and visualization,
  - machine learning (ML)
  - modelling and simulation of complex systems
  - high-performance computing (HPC)

• Program for research fellows in residence.
• Development of a concept for guiding transdisciplinary research between the CSH member institutes.

Apart from the institutes and departments involved with the CSH initiative, the Module “Data and Statistical Consulting (DSC)” of the Core Facility Hohenheim will be located at Steckfeldstraße 2. The module provides various services:

• Providing access to commercial and official economic and financial data sources (e.g. Refinitiv EIKON, CRSP, WRDS).
• Scientific counceling regarding statistical and econometric questions and the application of quantitative empirical methods,
• as well as support during all stages of empirical research projects, particularly in business, economics and the social sciences.