Data4Moz: Analyzing Data for Societal Impact in Mozambique

Data4Moz is one of the key partners in Africa (Early Adopters) of the LUISA project, funded by the European Space Agency.

Data4Moz’s participation involves leveraging its expertise to address critical challenges in natural resource management and sustainable development. In the heart of Mozambique, Data4Moz is making waves through its innovative approach to data management and geospatial analysis. By integrating geospatial data and advanced technology, Data4Moz seeks to empower decision-makers with precise
insights, enabling more informed planning and sustainable development across the country. Their mission centers on collecting comprehensive data and leveraging it through innovative spatial analysis, transforming raw information into actionable strategies for a resilient future. We had the opportunity to speak with Antonio Inguane, co-founder of Data4Moz, to learn more about their work, societal impact, and involvement in the LUISA project.

Decision-making powered by data

Data4Moz was founded with a mission to transform data into actionable intelligence that can drive positive change in Mozambique and the broader Southern African Development Community (SADC) region.

As Inguane explains, “We noticed that while there was a lot of data being collected, it wasn’t being used effectively to address the challenges faced by local communities. Our goal is to use this data to help governments and other entities make better decisions on how to invest and address the most pressing challenges for these communities”.
One of the core areas of Data4Moz’s work is natural resource management, particularly in rural communities. By combining demographic data with information on climate vulnerability, deforestation, and agricultural productivity, Data4Moz helps to paint a comprehensive picture of the socio-economic conditions in these areas.

Joining LUISA

The LUISA project, focused on land use and biomass management, saw a natural partner in Data4Moz due to their extensive experience and expertise in these areas. “We were motivated to join LUISA because it aligns perfectly with our mission to use data for sustainable development,” Inguane shares.

The role of Data4Moz in this project involves modeling and analyzing the intensity of biomass usage in regions with different configurations of consisting of smallholder and commercial farmland, rangeland, and forest. By integrating various data sources, such as remote sensing and ground-level data, Data4Moz aims to provide insights into how different land use practices impact biomass and overall environmental health. This information is crucial for developing strategies to balance economic development with environmental conservation.

A future with AI

Looking ahead, Data4Moz has ambitious to expand its impact. “We see great potential to scale up our interventions across other regions in Mozambique,” Inguane notes. One of their next key milestones is to implement machine learning and artificial intelligence to enhance their data analysis capabilities. By doing so, they hope to provide even more reliable and actionable insights that can drive sustainable
development. In the context of the LUISA project, Data4Moz aims to use the platform to inform local
governments and communities about the best practices for land and resource management. “We believe that the results from LUISA will help guide interventions that can improve land productivity and environmental sustainability,” Inguane adds.

Partner up

Data4Moz works closely with academic institutions, NGOs, and government bodies to maximize their impact. “The value of collaboration is immense, especially for a social enterprise like ours,” Inguane emphasizes, “By partnering with institutions like the University of Twente, we gain access to cutting-edge research and technology, which enhances our ability to deliver high-quality data and insights.”
For those interested in supporting or collaborating with Data4Moz, you can connect with them through their website or their active LinkedIn page.