Data and Displacement: Assessing the Practical and Ethical Implications of Targeting Humanitarian Protection Data-driven practices of targeted humanitarian protection are in urgent need of assessment, since these raise a range of practical and ethical questions that directly impact at-risk populations. While the targeting of protection needs through the production of data is common practice, the proliferation of large-scale quantitative, biometric and visual data within the humanitarian field is unprecedented. Established in 2014, there are presently 10,055 datasets for 253 locations from 1219 sources on the Humanitarian Data Exchange (HDX). This project produces a timely and robust analysis of data-driven protection targeting, focusing on two contexts that are characterised by conflict and high numbers of internally displaced persons (IDPs): northern Nigeria and South Sudan. It does so by assessing the implications of the production and use of large-scale data in targeting humanitarian protection, particularly on those most directly affected by such developments: IDPs themselves.

The increasing production and use of large-scale data is not unique to the field of humanitarianism. However, the stakes are particularly high when it comes to data-driven practices of targeting protection for those most at risk. Humanitarian interventions are designed to protect the most vulnerable groups, hence any misuse or miscalculation in the use of data can have a drastic effect on at-risk populations. Careful assessment of the practical and ethical implications of data-driven targeting of protection is thus foundational. It is often assumed that humanitarians can be trusted more than commercial organisations or governments in collating and using large-scale data, due to their mandate of 'do no harm'. Yet it is vital to examine the potential risks, exclusions and biases or vulnerabilities implicit in the production and use of such data. While data can enable quicker, efficient and improved evidence-based responses, critical questions surrounding processes of data collection and what counts as evidence, the ethics of data collection and its use, and the accountability and protection of the data produced in contexts of vulnerability are increasingly necessary.

Our research addresses these questions based on the research team's combined interdisciplinary academic and operational expertise. The project brings together academic researchers from the UK and Nigeria with practitioners from the International Organisation for Migration - the United Nations Migration Agency, which is responsible for the Displacement Tracking Matrix (DTM). DTM is the system deployed to track and monitor displacement and population mobility, and forms one of the largest data collectors on IDPs globally. Our project examines the work of DTM in the context of wider datasets used for the targeting of humanitarian protection in northern Nigeria and South Sudan. It focuses on practical and ethical challenges that arise in the collection and use of such data, and undertakes in-depth research with local stakeholders and internally displaced communities. The project asks: How effective is the data-based targeting of humanitarian protection in practice? Who benefits from such practices - and who is excluded? And how can the data-driven targeting be developed to reduce the chances of vulnerable groups falling through the cracks of humanitarian protection?

The project contributes: an interdisciplinary perspective on the practical and ethical implications of data-driven humanitarian targeting in sub-Saharan Africa; an operationally-driven analysis of the efficacy of data-driven humanitarian protection in contexts of conflict and displacement; a qualitative assessment of the impacts of the production and use of large-scale data for at-risk populations; and methodological insights regarding the utility of mixed methods approaches for the analysis of large-scale data. Research and development activity contributing to the UK’s strategy to address key development challenges.