Data Science for Innovation Unit

The research unit "Data Science for Innovation" develops digital tools for knowledge transfer and thus supports the innovative capacity of industry and research. To this end, the researchers build up an extensive data base and develop intelligent applications based on it using machine learning and network analyses. With their competencies in the field of data science and artificial intelligence, they support other researchers and companies and can contribute significantly to the successful transformation of economic and social structures.

Scientific Library on Regional Development

In this scientific infothek, you will find bundled information on how research contributes to successful structural change. We report on scientific models, instruments and procedures for regional development and transformation processes and the resulting policy advice. This page is updated regularly. If you have any comments, please feel free to contact the editors.

 

Scientific Library on Regional Development

Publications

YearTitle/AuthorDocument Type
2021Ausgründungen aus der außeruniversitären Forschung: Gründungsdynamik und Erfolgsbedingungen im Ost-West-Vergleich
Kahl, Julian; Dornbusch, Friedrich; Pohle, Anna; Trela, Karl; Weiße, Marlen; Druffel, Christina (Mitarb.)
Study
2021How to Find New Industry Partners for Public Research: A Classification Approach
Trela, Karl; Campbell, Yuri; Dornbusch, Friedrich; Pohle, Anna
Journal Article
2020Too big to see: Exploring proxies of structure in a real large-scale university-industry cooperation network
Campbell, Yuri
Preprint
This publication list has been generated from the publication database Fraunhofer-Publica.