Checklist: 10 guiding principles for effective use of risk data

Effective decision-making in disaster risk management requires good risk data. That’s why at the Global Facility for Disaster Reduction and Recovery (GFDRR)’s Open Data for Resilience Initiative (OpenDRI), our work focuses on improving processes surrounding the dissemination, creation, and communication of risk data—from using drones to map flood vulnerability in Niger to building a geospatial data sharing platform in Bangladesh.

Local city officials and university students in Can Tho, Vietnam
collaborate and learn about innovative mapping technology
Photo credit: Robert Banick/GFDRR

And while much more progress is needed to improve the quality and availability of risk data, the good news is that governments, international agencies, and scientific institutions are increasingly making their data open and available to planners, civil contingency managers, and responders. Combined with advances in technology, the movement for open data is generating an unprecedented volume of risk data. OpenDRI’s Open Data for Resilience Index monitors this trend by tracking the existence, availability, and openness of data on disaster risk and resilience worldwide.

One key challenge now is how best to capture, analyze, and communicate this data to inform decision-making. In an effort to provide a framework to guide the use of data in disaster risk management, OpenDRI has developed 10 principles that can be applied throughout a project’s life cycle to help ensure that risk data is used effectively for decision-making. Below, we break down these guiding principles and provide practical examples of how they have been applied.

  1. Put users at the center of project design

Risk information must be grounded in the needs of users at relevant geographic and time scales and provided through accessible and understandable formats. In a successful example of this practice, UNDP Myanmar’s SESAME (Specialized Expert System for Agro-Meteorological Early Warning) drew on local cropping practices to develop location-specific agro-advisories which covered multiple timescales.

  1. Engage inclusively with affected populations

It is also critical that risk information addresses the needs of those people most directly impacted by natural hazards through active collaboration. Case in point: Resilience.IO, an open-source computer-based platform spearheaded by the Ecological Sequestration Trust, used collaborative laboratory workshops to help identify local stakeholders’ priorities.

  1. Cultivate a shared understanding of the problem

Consensus among the providers and users of risk information about the core problem that a project seeks to address will support the development of understandable, decision-relevant risk information. OpenDRI’s Serious Games have, for instance, used a simulated game to enable diverse stakeholders to gain a shared understanding of the challenges being addressed by risk data.

  1. Co-create data with users of risk information

The generation of data and information with help from users of risk information strengthens long-term risk data creation, builds trust, and increases ownership of the risk information outputs. For example, the Togo Red Cross developed the FUNES flood risk forecasting tool and co-created daily flow data with dam operators.

  1. Promote openness in data sharing, coding, and innovation

A policy of ‘open by default’ for data sharing, coding, and innovation processes will support local ownership of risk information and scalability of the risk information project. For instance, the GFDRR-supported InaSAFE hazard prediction software in Indonesia uses open source QGIS software, giving developers the opportunity to customize the software based on local needs, at a cost that isn’t prohibitive.

  1. Understand the users of risk information

Cultural, social, cognitive, and psychological factors influence how individuals perceive and respond to risk information. With this in mind, producers of Amrai Pari, an Indian reality television show designed to raise awareness on the importance of building community resilience, used extensive audience segmentation to better understand the needs and preferences of its viewers and adapted their project based on the local culture.

  1. Select appropriate communication channels for communicating risk

In order to reach the widest population possible, channels for communicating risk information should be accessible, trustworthy, interactive, scalable, and resilient to natural hazards. The Circle risk assessment tool, developed by Deltares, has both a digital version and a simplified non-digital board version.

  1. Ensure that strategies are sustainable

The effective use of risk data requires a viable and sustainable business model combined with support from local communities and networks. The Forecast-based Warning, Analysis, and Response Network (FOREWARN), a global network of risk analysts, provides mentoring on early warning and response to non-members as a way to ensure that its efforts are sustainable.

  1. Encourage a culture of continuous learning and self-assessment

The ongoing relevance of a risk information project will be determined by the degree to which it develops a project culture of ongoing learning, review, and self-assessment to identify what is working and what is not. In Malawi, GFDRR’s working group for the  Malawi Spatial Data Platform (MASDAP), strives to embed this culture by meeting regularly to update and improve the platform.

  1. Generate dialogue and debate

The key indicator of the impact of risk information on decision-making is the degree to which it generates discussion by the users of that information. OpenDRI’s Serious Games, for instance, fostered robust dialogue between users of risk information—government officials, experts, and non-experts alike—over the course of a simulation of a flood scenario for the city of La Plata, Argentina.

Interested in open data for resilience? These 10 guiding principles are the foundation of OpenDRI’s Design for Impact framework, which aims to provide project designers with a framework to guide them in using risk data for disaster risk management. Check it out!

Author: Simone Balog-Way. Co-authors: Vivien Deparday; Lorenzo Piccio.
This piece was originally published on the World Bank Group Data Blog.