Ufuoma Ovienmhada and Danielle Wood, along with their colleague from Green Keeper Africa, Fohla Mouftaou, published a peer-reviewed journal article with the journal Frontiers in Climate.
Summary: “Inclusive design of Earth observation decision support systems for environmental governance: a case study of Lake NokouÃ©”
Earth observation (EO) data can improve understanding of human-environmental systems for building climate data services, or decision support systems (DSS), to improve monitoring, forecasting and mitigation of climate damage. However, OT data is not always integrated into decision-makers’ workflows for a multitude of reasons, including models of awareness, accessibility and collaboration. The aim of this study is to demonstrate a collaborative model that addresses historical power imbalances between communities. This article highlights a case study of a DSS climate damage mitigation collaboration between the Space Enabled research group at MIT Media Lab and Green Keeper Africa (GKA), a company located in Benin. GKA addresses the management of an invasive plant species that threatens ecosystem health and economic activities on Lake NokouÃ©. They do this through a business model of social entrepreneurship that aims to advance both economic empowerment and environmental health. Demonstrating a Space Enabled-GKA collaborative model that advances GKA’s business goals, this study first considers several popular technology and service design methods and offers critiques of each method in terms of its ability to address the inclusiveness in complex systems. These critiques led to the selection of the Systems Architecture Framework (SAF) as the technology design method for the case study. In the remainder of the document, the SAF is applied to the case study to demonstrate how the framework co-produces knowledge that would inform a DSS with Earth observation data. The document offers several practical considerations and values âârelated to epistemology, data collection, prioritization and methodology to achieve inclusive design of climate data services.