Collected documentation, references and links for the projects and each of the library components.
Current technical document and published reports
Schema contents and structure, providing guidance on completing metadata according to the schema.
Solving the Puzzle provides a community perspective on priorities for future collaboration and investment in the development and use of disaster risk information for developing countries. The focus is on high-impact activities that will promote the creation and use of risk-related data, catastrophe risk models, and platforms, and that will improve and facilitate the understanding and communication of risk assessment results.
This paper, a background paper for the UNISDR (now UNDRR) Global Assessment Report 2019, gives an overview of the first phase of development under the Challenge Fund.
Reports documenting development under the DfID Challenge Fund
An international consortium led by British Geological Survey (BGS) undertook the challenge of developing an open schema for multi-hazard scenario footprints in response to recommendations from Solving the Puzzle, and populating it with data for scenarios in Tanzania.
An international consortium led by the Global Earthquake Model Foundation (GEM) undertook the challenge of developing an open, multi-scale exposure data schema for multi-hazard analysis (GED4ALL) in response to recommendations from Solving the Puzzle. It was populated with data for Tanzania and other selected countries.
An international consortium led by University College London (UCL) EPICentre undertook the challenge of developing an open data schema for multi-hazard, physical fragility and vulnerability relationships, and socioeconomic indicators and indexes in response to recommendations from Solving the Puzzle. The schema was populated with earthquake physical vulnerablity and fragility relationships.
GeoSolutions undertook the challenge of developing an open risk data dashbaord in response to recommendations from Solving the Puzzle, intended to visualize the contents of the hazard, exposure and vulnerability schema.
GEM and UCL EPICentre updated the existing schema and developing a new component to store modeled loss curves and loss maps.
GEM and UCL EPICentre further updated the existing schema and refactored the vulnerability schema to establish a unified database and common tables linking all schema.
Risk Data Library on GitHub
The Risk Data Library is a system for better managing risk data. Its components make working with risk data easier and create an effective library system designed explicitly for storing, finding, editing and exchanging data for disaster risk assessments. The two components are now available: The RDL schema is a new language for describing hazard, exposure, vulnerability and loss data. It gives risk experts a single language to describe datasets used in climate and disaster risk assessment. The datasets have an underlying consistency that makes them highly interoperable, and key metadata fields tailored to risk analysis. The RDL database enables hazard, exposure, vulnerability and loss datasets to be stored in the same environment, consistent with the schema. It provides the architecture for searching and downloading the increasing number of datasets using the schema.
The Risk Data Library project is led by GFDRR Labs. The Global Facility for Disaster Reduction and Recovery (GFDRR) is a global partnership that helps developing countries better understand and reduce their vulnerability to natural hazards and climate change. GFDRR Labs uses cutting-edge science and technology to make high-quality risk information available faster and at lower costs, and develop new tools that allow decision-makers and communities to collect, share, and understand risk information. We tailor our approach to support the full range of disaster risk management interventions — from preparedness to risk reduction to consideration of financial solutions.
Uploading data on riskdatalibrary.org is limited to GFDRR administrators. The Risk Data Library is not intended for public upload of data.