Addressing Inequitable Openness in Licences for Sharing African Data and Datasets Through the Nwulite Obodo Open Data Licence
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University of Pretoria
South Africa -
Strathmore University Kenya
Abstract
This article examines the relationship between Standard Public Open Licences (SPOLs) and inequity in the artificial intelligence (AI) innovation ecosystem, focusing on how these licences affect access to and use of African datasets. While SPOLs are widely promoted as tools for democratising data access, they often apply uniform conditions to all users, disregarding disparities in infrastructure, capacity and socioeconomic context. As a result, SPOLs may unintentionally reinforce exclusion and enable extractive data practices that disadvantage communities contributing valuable datasets that they have preserved and curated through historically challenging conditions. The study employs a desktop literature review of primary and secondary sources, complemented by analysis of specific case studies from the Masakhane Research Collective in Natural Language Processing and qualitative vignettes based on real-world experiences to identify inherent and systemic limitations of current SPOLs. The research shows how existing SPOLs, particularly those founded on copyright law, fail to accommodate the positionality of African and similarly situated users in the global data economy. In response, the article introduces the Nwulite Obodo Open Data Licence (NOODL Licence), a novel, tiered SPOL designed to foster equitable openness. NOODL differentiates conditions of use based on users’ geography and development context, incorporating benefit-sharing obligations and context-sensitive terms. It maintains the simplicity and legal clarity of existing SPOLs while addressing their inequities. By critically analysing the overlooked relationship between SPOLs and inequity, this article contributes a practical, context-aware licensing alternative that centres communities. While grounded in the African experience, the NOODL framework offers a replicable model for promoting fairness and inclusivity in global data governance and AI innovation.
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Author Biographies
Chijioke I Okorie is Associate Professor at the University of Pretoria, South Africa, and the Principal Investigator of Data Science Law Lab, a research network that deploys research in law and produces evidence and policy advice to support the growth of data science and AI research across Africa. Chijioke led the development of the Nwulite Obodo Open Data License for sharing African datasets openly and equitably. Chijioke is an Associate Editor of South African Intellectual Property Law Journal, and the author of several articles on intellectual property and innovation law issues in Africa.
Dr. Melissa Omino is the Director of the Centre of Intellectual Property and Information Technology Law at Strathmore University, the leading Eastern African AI Policy Hub and Data Governance Policy Centre. Her research direction is focused on utilizing both an African lens and Human Rights lens. Dr. Omino’s research aims to determine the nature and focus of African AI. She co-developed the Nwulite Obodo Open Data License for sharing African datasets openly and equitably and is an IP expert with experience as an Advisory Board member in several projects involving AI and IP, a National AI Strategy Process and leading the IP Advisory to global entities funding AI research in Africa.
