Is Danish research ready for data-driven interdisciplinarity?
Data-driven research is rushing forward with enormous potential, but is easily drowned in practice. Thomas Gammeltoft-Hansen, Head of the Center of Excellence for Global Mobility Law, University of Copenhagen, and Thomas Moeslund, Head of the AI for the People Center, Aalborg University, have therefore gathered representatives from the research world to share their experiences and recommendations in a new report.
The opportunities for interdisciplinary research using machine learning and big data have grown significantly in recent years. In a wide range of disciplines, access to data and new methods allow for scientific breakthroughs with broad applications in both basic and applied research. But with so many possibilities, it's easy to stumble and get lost.
In practice, interdisciplinary research using big data and machine learning is still a relatively new phenomenon. Many researchers have paid a high price along the way, as there are often a number of challenges associated with initiating and conducting this type of research.
According to Gammeltoft-Hansen and Moeslund, "Wise minds and sharing of experiences have taught us some lessons. The experiences express both the interdisciplinary development in the research community and point towards a number of recommendations for further work with interdisciplinary, data-driven research, including AI."
Read the full article in Danish here.