UNDP
Global Risk Anticipation Data Hub
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ABOUT
The Risk Anticipation Data Hub, a project of the United Nations Development Programme (UNDP), is a transformative open-access data platform. A ready-to-use data warehouse for over 15,000 indicators combines processed and cleaned public datasets on a multitude of risk factors. Equipped with state-of-the-art technology, including a generative Artificial Intelligence (AI) interface and real-time analytics, the Data Hub empowers ecosystem partners with data and insights for better crisis anticipation, prevention, and response.
OBJECTIVES
With support from CRAF'd, UNDP elevates its internal Crisis Risk Dashboards to a critical global crisis data infrastructure and digital public good. It addresses significant gaps in the ecosystem by providing open access to cleansed and pre-processed risk data through its data warehouse. The generative AI interface and real-time analytics capability mark a significant leap forward in global, evidence-based crisis action and sustainable development efforts.
When it comes to anticipating risks and responding to crises, we all want reliable, up-to-date information to guide our decisions. The Risk Anticipation Datahub provides exactly that – converting vast amounts of data into insights that help us act earlier and more effectively.
Shoko Noda
Assistant Secretary-General and Director, Crisis Bureau, UNDP
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UPDATES
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LAUNCH OF THE RISK ANTICIPATION DATA HUB
UNDP soft-launched the Risk Anticipation Data Hub (RADH), at the Data for Peace Conference, creating a centralized data warehouse and API infrastructure for integrated risk analysis across multiple sectors. RADH is a one stop shop for standardized development risk indicators powered by Google Data Commons.
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CRISIS RISK DASHBOARDS
At the Data for Peace Conference, UNDP presented Crisis Risk Dashboards used across country offices to visualize risk and inform early warning. With CRAF’d support, the data behind the dashboards helps partners anticipate, prevent, and respond with timely, targeted insight.
