Exploring future challenges for big data in the humanitarian domain

Abstract

This paper examines the challenges of leveraging big data in the humanitarian sector in support of UN Sustainable Development Goal 17 “Partnerships for the Goals”. The full promise of Big Data is underpinned by a tacit assumption that the heterogeneous ‘exhaust trail’ of data is contextually relevant and sufficiently granular to be mined for value. This promise, however, relies on relationality – that patterns can be derived from combining different pieces of data that are of corresponding detail or that there are effective mechanisms to resolve differences in detail. Here, we present empirical work integrating eight heterogeneous datasets from the humanitarian domain to provide evidence of the inherent challenge of complexity resulting from differing levels of data granularity. In clarifying this challenge, we explore the reasons why it is manifest, discuss strategies for addressing it and, as our principal contribution, identify five propositions to guide future research.