When we think about sustainability and sustainability issues, we most often think with and through data. Data is to a large extent used to steer consumption patterns towards more sustainable ones. In Human-Computer Interaction (HCI) research, the most common approach has been eco-feedback i.e., digital displays of data on consumption and/or impact of consumption. However, the acknowledgement that people are not rational agents who change their behaviour in predictable ways when becoming cognitively aware of consumption patterns, has led to calls for alternative approaches. In this dissertation, Martin suggests an approach seeks to represent data with people to foster engagement and action towards sustainable consumption. In doing so, three central research questions are addressed: 1) What characterises data interactions for sustainable consumption? 2) How do people use data to make sense of sustainable consumption? and 3) How can we foster sense-making and engagement in sustainable consumption through data interactions?

Data interactions for sustainable consumption can be characterised in two dimensions. The first dimension is sustainable consumption which is motivated by two purposes: understanding (un)sustainable consumption and changing unsustainable consumption patterns. The second dimension is interactions with data which can be separated into interactions with digital and physical data representations. Martin finds that the form of the data (i.e. digital or physical) plays a large role in how people use it in sense-making processes. Digital data for sustainable consumption is often more precise and exhaustive than data in physical form; however, it does not foster engagement as it is often represented through interfaces with low operationality, and ambiguity tends to be hidden through interfaces that represent digital data. The dissertation outlines physical data interactions that focus on embodiment and reification through physicality as an alternative to digital data interactions for sense-making processes as they allow people to ‘stay in the interactions’ with both the data itself and the issues that the data depicts in ways that are highly engaging.

Members of the assessment committee are Associate Professor Cecilia Katzeff, KTH Royal Institute of Technology (Sweden), Associate Professor Jonas Fritsch, IT University of Copenhagen (Denmark), and Associate Professor Florian Echtler (chairman), Aalborg University (Denmark). Supervisor for the thesis has been Professor Mikael B. Skov, Aalborg University. Co-supervisor for the thesis has been Associate Professor Dimitrios Raptis, Aalborg University. Moderator Associate Professor Timothy Merritt.

All interested parties are welcome. After the defense the department will be hosting a small reception in cluster 5.