The research outlined in this paper is focusing on understanding asylum decision-making and outcome variations across the Nordic countries. As a preliminary study, we extract data from an open dataset1 of decision summaries from the Danish Refugee Appeals Board. The approach we propose, offers points for discussion of how prototyping context and participation can help raise questions about such data and engage stakeholders. Combining the application of Machine Learning (ML) and Natural Language Processing (NLP) with participatory methods (e.g. critically designed artefacts) enable us to 1) move beyond “obvious” ML-application areas, 2) through sensemaking of data with stakeholders, and 3) co-develop approaches to data science from a CSCW-perspective. en
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