Narratives and Counternarratives on Data Sharing in Africa

TL;DR

This paper critically examines the narratives surrounding data sharing in Africa, highlighting complex socio-political barriers and proposing nuanced perspectives to improve data sharing practices on the continent.

Contribution

It introduces counternarratives based on African experts' perspectives, challenging dominant deficit narratives and emphasizing socio-historical factors affecting data sharing in Africa.

Findings

Power imbalances from colonial legacies influence data sharing.

Western-centric policies often misalign with African contexts.

Trust and acknowledgment issues hinder equitable data sharing.

Abstract

As machine learning and data science applications grow ever more prevalent, there is an increased focus on data sharing and open data initiatives, particularly in the context of the African continent. Many argue that data sharing can support research and policy design to alleviate poverty, inequality, and derivative effects in Africa. Despite the fact that the datasets in question are often extracted from African communities, conversations around the challenges of accessing and sharing African data are too often driven by nonAfrican stakeholders. These perspectives frequently employ a deficit narratives, often focusing on lack of education, training, and technological resources in the continent as the leading causes of friction in the data ecosystem. We argue that these narratives obfuscate and distort the full complexity of the African data sharing landscape. In particular, we use storytelling via fictional personas built from a series of interviews with African data experts to complicate dominant narratives and to provide counternarratives. Coupling these personas with research on data practices within the continent, we identify recurring barriers to data sharing as well as inequities in the distribution of data sharing benefits. In particular, we discuss issues arising from power imbalances resulting from the legacies of colonialism, ethno-centrism, and slavery, disinvestment in building trust, lack of acknowledgement of historical and present-day extractive practices, and Western-centric policies that are ill-suited to the African context. After outlining these problems, we discuss avenues for addressing them when sharing data generated in the continent.