Together, we have written this article to bring together our different experiences and perspectives to paint a comprehensive picture of the impact of tourism in Berlin.

This article was written with the motivation to investigate and illustrate the complex effects of increasing tourism in Berlin. Given the rapid changes in the city, we wanted to shed light on how the influx of tourists affects different aspects of urban life, from rent prices to the quality of life of residents. We chose this topic because we are all connected to it in our own way: one of us was born and raised in Berlin, two of us moved here to study - Guolong even came from abroad. We have all had different experiences and have been both tourists and residents.

The topic of "tourism" is perceived both very positively and very negatively. That's why it was important for us to shed light on both sides and provide alternatives and food for thought.

We've worked closely with various experts and institutions to produce this article.We would like to briefly introduce you to those we have worked with directly:

It all started with the Urban Journalism Network, our primary data partner throughout the entire course. We initially explored projects, data sets, and data visualizations, which led us to our topic—though it started in a form quite different from what it eventually became. Our contacts were Gaby Khazalová, Virginia Vargolska, and Hendrik Lehmann, who was involved with the project from the beginning as he co-led the course. This close collaboration not only provided us with access to additional data sets but also inspired us to explore new perspectives and topics, shaping the article into its final form.

In addition to UJN, we maintained regular contact with other companies and organizations. For example, we connected with Empirica, a research institute in Berlin, to gain a more detailed understanding of the housing situation in the city, particularly at the district level. Through this partnership, we gained access to a complex data set that significantly enriched our research.

Hendrik also facilitated our connection with Terralytics, who provided us with data on movement and stays within Berlin. Our initial goal was to use this data to identify hotspots in the city and compare them with Empirica’s data to recognize patterns. Unfortunately, we were unable to filter the data in the way we needed, which led to us largely removing this aspect from our article.

The data from Inside Airbnb was particularly helpful, especially for our research on short-term rentals. This data allowed us to better understand the challenges surrounding short-term rentals in relation to legislation. Additionally, since much of the data was already visualized, it made it easier for us to compare different cities, ultimately saving us a lot of time during the project.