Matokeo – Data Collection On Artisanal and Small-Scale Mining in Eastern DRC

ASM miners looking at mobile phone

Written by Ulula

October 27, 2022

The following is an excerpt taken from the full report, accessible here.

‘Matokeo’ (meaning ‘impact’ in Swahili) is a data-driven platform operating in the Democratic Republic of Congo (DRC) with the ability to reach last mile artisanal miners, enabling them to ping the latest international price of gold. Conceptualized by Ulula and the International Peace Information Service (IPIS), the project won a Conservation X grant in October 2020 for its ability to remotely collect data about mercury-use, deforestation, child labor and security issues. Using Ulula’s system of two-way mobile based engagement, Matokeo enabled a more continuous impact data collection through automated mobile surveys focusing on the above-mentioned indicators.

Since 2018, IPIS and Ulula developed a mobile-based incident reporting mechanism called ‘Kufatilia’ (which means ‘to track’ in Swahili). By sending the key word ‘Kufatilia’ to toll-free local phone numbers from a Congolese telephone line, anyone can report an incident linked to the exploitation, transport or export of minerals. The incidents are then visible in a secured online-platform to a network of 20+ Civil Society Organizations (CSOs) active in Eastern DRC.

In 2020, the Conservation X grant allowed Ulula and IPIS to develop the second stage of this data platform, by introducing the keyword ‘Matokeo’. Conceived both as a way to increase user participation and to remotely collect data on the impact of artisanal mining on local communities in Eastern DRC, Matokeo was built with three components:

  • Price Ping
  • IVR automated surveys
  • Broadcast messages

The entire program is available in three languages — Swahili, Lingala and French. Participants can select their preferred language during the surveys and their choice is remembered by the platform.

To learn more about Matokeo, read the joint report by Ulula Program Manager, Aparna Moitra, and Data Analyst Dion Chang in collaboration with IPIS here.

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