Data walking in Klagenfurt

How do districts differ in terms of building and hedge height and what does this tell us about affluence? Where are the servers located, that QR codes in Klagenfurt link to and how are they globally distributed? How is noise and pollution (unequally) present in the city and what quality criteria can be established for measurement and interpretation? These are some of the questions that a group of MA and PhD students from the Universities of Klagenfurt and Graz investigated on a data walk – with inspiring insights.

The data walk was part of the course Digital Data Sprint , co-taught by Katharina Kinder-Kurlanda (D^!ARC, University of Klagenfurt) and Juliane Jarke (BANDAS-Center, University of Graz) in collaboration with Laura Kocksch (Aalborg University) and Mace Ojala (Ruhr University Bochum). The course introduced PhD and advanced MA students to the field of Critical Data Studies, exploring and reflecting different methodological engagements with digital data, processes of datafication and data-related practices.

 

After an introduction to Critical Data Studies and learning about different forms of data walks and various research data management topics and solutions, the participants planned and conducted their own data walks and made sense of the data in a data sprint segment. They showed great creativity in their engagement with the city and how they worked not only with data and infrastructure but also tackled their own assumptions.

 

Data walks are a creative method in Critical Data Studies (Wieringa and van Es, 2018; Jarke 2019) as well as in Participatory Design (Kanstrup et al. 2014). They facilitate embodied ways to study datafication, to sense, reflect and experiment with the situatedness of data and to generate new angles for further exploration. In the data sprint segment, students worked on one or more digital data sets, analyzing the data with the aim of jointly developing possible research questions. Sprinting refers to the aim to achieve results with data within a relatively short time frame, focusing on the reflection of opportunities provided by methods and data (Kocksch et al. 2022).

 

This will not have been the last opportunity for data walking in Klagenfurt – the course format will be offered again in the future at the D^!ARC.