For best experience please turn on javascript and use a modern browser!
You are using a browser that is no longer supported by Microsoft. Please upgrade your browser. The site may not present itself correctly if you continue browsing.
Each month, the Spotlight introduces a Data Science Centre Affiliate Member. This month, meet Stefanie Boss, PhD Candidate at the Institute for Information Law and the Informatics Institute.

Can you tell us more about your role and how you apply data science to your projects?

I am an interdisciplinary PhD Candidate at the Institute for Information Law, the Institute for Informatics, and affiliated with the Data Science Centre. I work at the intersection of law, economics and data science - more specifically, in the realm of compliance and incentive-related behavior in digital ecosystems. In my research, I use data science as a methodology to support my empirical research agenda. For instance, I apply it to look into behavioral aspects of compliance.

An important focus of my PhD is building a bridge between legal research and data science methodology, and experimenting with these methodologies to determine which are effective for legal research.

Is there a project from this past year that you are most proud of?

I recently completed a project on compliance behavior in the Ethereum ecosystem, working with a colleague to gather and analyze real-world data around the moderation of sanctioned transactions by Ethereum actors. I integrated various methodologies – including statistics and anomaly detection tools - to draw conclusions about compliance behavior. The project was selected for presentation at an IEEE conference this summer, and will result in the publication of a short paper. I hope to apply parts of this methodology in future projects as well.

What do you like most about being a DSC member?

I appreciate the opportunity to participate in courses and workshops on methodology, which are really helpful when you’re still developing your methodological skills. I also recently attended an event with other Data Science Centre PhD’s, which was a great way to learn from each other’s experiences, discuss methods, and enjoy the benefits of an interdisciplinary environment.

What is your favourite data science method?

At the moment, I like to use anomaly detection tools for my research, but I’m eager to keep expanding my knowledge.

Are you camp Python/R/or something else?

Python, 100%! It’s super versatile.

Mr. drs. S. (Stefanie) Boss

Faculty of Law

Information Law