Prediction and data curation in digital humanitarianism

Our article contributes to debates on critical humanitarianism and critical dataset studies by examining the praxis of digital humanitarianism and the entanglement between what we know and how we know human suffering in large-scale disasters. We specifically focus on the “data work” carried out by various professionals in creating and curating datasets used by humanitarian actors to address both current and future crises. In doing so, we explore how these actors make sense of the development, maintenance and (re)use of such datasets. This approach enables us to analyse the underlying principles and practices of data curation and to investigate the challenges that arise when humanitarian and non-humanitarian actors collaborate to produce and sustain these datasets. We also examine how these often tension-filled collaborations influence practitioners' understandings of humanitarian crises and their efforts to reconcile efficiency with humanitarian principles. We argue that while there is no such thing as a “humanitarian dataset”, there are contested processes of datafied humanitarian knowledge production that are situated in specific contexts. We suggest that the construction of these datasets redefines humanitarian knowledge production and is therefore critical to understanding the shifting politics of digital humanitarianism. Our findings highlight three key challenges that characterise the relationships among these groups: the fragmentation of the humanitarian data value chain; the asymmetries in expertise and skills among the diverse professionals involved in dataset curation; and the integration of small and big data in crisis analysis and prediction. These insights carry both epistemic and ethical implications, drawing attention to the problematic relationship between datafication and humanitarian principles.