New funding lines for interdisciplinary researchFunding for research into inflation and vaccine willingness

27 July 2023, by Christina Krätzig

Photo: CC0

How does the media report on inflation? A project investigating exactly this has been recently funded. Another project is using three-dimensional spatial modeling to look at the process of exchange in teams.

A new funding line is allowing Universität Hamburg researchers to develop interdisciplinary research at the interface between digital methods and specialist knowledge. The first round provides funding for 6 cross-disciplinary labs (CDLs).

The House of Computing and Data Science aims to introduce and develop digital methods in all research disciplines at Universität Hamburg. Researchers will not only be supported in their use of digital tools, but support is also provided for interdisciplinary research between developing methodologies and applications.

In the new cross-disciplinary labs for example, the Hamburg Center for Health Economics is working with the Faculty of Humanities and the Faculty of Business Administration to examine public debates on vaccine willingness and analyze these using machine learning methods. Researchers in the Faculty of Mathematics, Informatics and Natural Sciences and the Faculty of Business, Economics and Social Studies are working together on a project in which they examine vast quantities of text for language specific to inflation. They are also taking a closer look the inflation narratives put forward by the media.

The interdisciplinary research in the DCLs will be funded to a maximum of €160,000 per year, to provide the projects with uncomplicated start-up funding. This funding line may also consider projects funded by other sources, to achieve a greater reach, better networks, and expanded services and advice from the Method Competence Center. In turn, the projects are expected to share their experience in the spirit of sustainable research with the Method Competence Center, to allow future projects to benefit from the resulting expertise.

Both sides benefit from this collaboration: methodological sciences often focus on theoretically-framed tasks in modeling and automating, while in practice researchers are always faced with novel problems where standard solutions do not work and either need to be either adapted, or a new class of tasks found. Researchers often do not know what new technology is available for their field of application, and they also need help interpreting the automatically-generated results. The work in cross-disciplinary labs is to foster collaboration between all participants on an equal footing, both in terms of methodology and applied scientific results.

The House of Computing and Data Science and cross-disciplinary labs will be funded through the Excellence Strategy of the Federal and State Governments, among other sources.