Summary
The MUNDI MSCA project explores the uses of digital innovations for the predictive anticipation, real-time analysis, and early intervention in multiple and intersecting threats to human security in Ghana. Specifically, the project takes the focal areas of Ghana’s multi-sectoral emergency preparedness and response effort – that is, the spread of infectious disease, climate-change related flooding, and man-made disasters in the context of mining activities – as case studies to explore data practices in the country’s national disaster risk reduction (DRR) strategy. Central tools of DRR, including strategic and evidence-based risk assessment, operational plans and risk communication, are directly tied to the systematic and standardized production and analysis of data about populations and their environs. This has raised concerns about data quality in contexts characterized by historically incomplete and fragmented population registers and statistical reporting systems. The MUNDI project seeks to answer the research question how innovations in data practices anchor the acceleration of interventions in human security in spite of multiple and layered uncertainties about data sources, models and predictions. Exploring this question in the context of Ghana will advance our empirical understanding of the base processes and material foundations of building “real-time” datafication in emerging data systems, develop new theoretical approaches to evidence-production under conditions of sustained uncertainty, and add to our methodological toolkit new frames for the comparative analysis of digital population data infrastructuring for the purpose of impact forecasting, early warning, and rapid deployment of first responders.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101103848 |
| Start date: | 01-09-2023 |
| End date: | 31-08-2025 |
| Total budget - Public funding: | - 230 774,00 Euro |
Cordis data
Original description
The MUNDI MSCA project explores the uses of digital innovations for the predictive anticipation, real-time analysis, and early intervention in multiple and intersecting threats to human security in Ghana. Specifically, the project takes the focal areas of Ghana’s multi-sectoral emergency preparedness and response effort – that is, the spread of infectious disease, climate-change related flooding, and man-made disasters in the context of mining activities – as case studies to explore data practices in the country’s national disaster risk reduction (DRR) strategy. Central tools of DRR, including strategic and evidence-based risk assessment, operational plans and risk communication, are directly tied to the systematic and standardized production and analysis of data about populations and their environs. This has raised concerns about data quality in contexts characterized by historically incomplete and fragmented population registers and statistical reporting systems. The MUNDI project seeks to answer the research question how innovations in data practices anchor the acceleration of interventions in human security in spite of multiple and layered uncertainties about data sources, models and predictions. Exploring this question in the context of Ghana will advance our empirical understanding of the base processes and material foundations of building “real-time” datafication in emerging data systems, develop new theoretical approaches to evidence-production under conditions of sustained uncertainty, and add to our methodological toolkit new frames for the comparative analysis of digital population data infrastructuring for the purpose of impact forecasting, early warning, and rapid deployment of first responders.Status
SIGNEDCall topic
HORIZON-MSCA-2022-PF-01-01Update Date
31-07-2023
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