Anglia Ruskin University
Mulder_2020.pdf (851.98 kB)
Download file

Humanitarian data justice: A structural data justice lens on civic technologies in post‐earthquake Nepal

Download (851.98 kB)
journal contribution
posted on 2023-07-26, 15:57 authored by Femke Mulder
As disasters are becoming increasingly datafied, social justice in the context of disasters is increasingly bound up with data. A data justice lens reveals how data projects and social justice interlink. This paper approaches social injustice in the context of disasters as structural inequalities in terms of resilience and risk. The first refers to people's ability to prevent, prepare for, respond to and recover from disasters, and the second to the probability that people will be exposed to hazards to which they are vulnerable. A data justice lens draws attention to the ways in which these structural inequalities shape humanitarian data projects. It also shows how such projects influence social justice outcomes. This paper shows how this lens can be applied to concrete disaster settings and the insights this yields for designers and project managers of data projects. This paper uses a qualitative case study approach to analyse two locally led civic technology projects in post-earthquake Nepal. These progressive initiatives sought to give disaster-affected people a role and a voice in the disaster response—and made a valuable contribution to response and recovery efforts. However, as they were rolled out in a context marked by stark social and digital inequalities, they still ended up primarily benefitting those who were relatively more resilient and less at risk. This paper explains why this happened and concludes by recommending critical and strategic collaboration with local progressive digital elites towards greater data justice in disaster settings.



  • Yes



Issue number


Page range


Publication title

Journal of Contingencies and Crisis Management





File version

  • Published version


  • eng

Legacy posted date


Legacy creation date


Legacy Faculty/School/Department

Faculty of Science & Engineering

Usage metrics

    ARU Outputs


    No categories selected