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Interview with Hanna Hottenrott

Interview |

Prof. Hanna Hottenrott, head of the Professorship of Economics of Innovation, gives a brief glance at her ongoing research, her fascination for data science and the changes it may bring in the future.

Hanna Hottenrott

What cutting-edge project are you working on right now?

We are currently working on a project in which we explore new ways of using web data for creating economic indicators. For instance, we model technology diffusion using information from company websites. This is particularly useful for new technologies such as additive manufacturing or block chain that are not easily traced with traditional indicators such as patents. In recent research we also show that networks between economic actors (companies, universities, other organizations) can be measured using data from professional networking platforms. These new data sources and novel network indicators will be extremely useful for economic research in the future.

What was the key experience that made you want to do research in data science and what fascinates you about working with MDSI?

There was not a single event that got me interested in data science. It was rather that I realized early in my PhD research that data science provides huge opportunities for economic research.

Being a member of MDSI is exciting because I get to see data science applications in so many different areas of research. For instance, meeting researchers at MDSI that work at the frontier of developing new network analysis methods was a great experience. The exchange with them was very inspiring and gave new ideas for our own research.

What paradigm shift do you expect within the next ten years, triggered in particular by the Institute's interdisciplinary approach?

Data science is interdisciplinary by nature because there are applications and new developments in virtually all disciplines from architecture to zoology. The rapid development in data science and advancement of methods as well as tools will likely benefit all fields of science. Yet, active exchange between data science researchers and data science users is extremely important for diffusing advances to the individual fields. By actively fostering and supporting exchange within and across fields, MDSI contributes to this important process.

And what else? (Wishes, curious moments in research, outlooks, future projects etc.)

I am looking forward to collaborating with other MDSI researchers in future projects, for instance, on new projects related to analyzing dynamic networks among companies.