OUTPUTS > PILOT / USE CASE 3

Supporting innovation based on global disaster risk data

In order to support decision making in case of natural disasters, there is an increasing interest in building comprehensive, open-data based  analytical models which include factors such as:

  • Changes in hazard scenarios.
  • Variation in human exposure.
  • Approaches in risk mitigation.

Summary

PROCESS will ease the work of experts thanks to its technical developments, so the user communities only need to focus on their desired presentation of the data. Therefore, it will make a contribution towards more efficient and collaborative ways of disaster risk data management.

Challenges

Information and risk management actions based on such complex models require collaboration among different organisations in activities of:

  1. Data generation.
  2. Data management.
  3. Validation of the analysis.
  4. Secondary use of data.

Methodology

Techniques and procedures

Approach:

    1st step: analysis of external reuse of data published, using PROCESS tools, in order to back the risk modelling  community.

    2nd step: development of a containerized and generalisable solution with a user friendly web-portal.

Resources

Key features

  • Loss calculation process:  several datasets, produced through different methodologies and in different repositories (initially at least).
  • Collaboration between research groups:  need for supporting versioning of the datasets as the process of cross-correlation and analysis uncovers opportunities for refinements and improvements in the accuracy of the models.
  • Showcase lifecycle support for disaster risk management data, in order to convince data producers to apply solutions interoperable with the PROCESS approach.

Results

For the field of activity

Main outcomes:

  • A containerized module which can be deployed on any storage site to expose data sets together with their meta data description.
  • A web-portal that can easily be configured and integrated with the PROCESS ecosystem, exploiting its capabilities of data placement the container can be efficiently deployed near the data that the projects want to publish.

For the entire project

  • Experience: the Use Case itself has shown that different communities have unique requirements on how their data should be made available and presented to the public.
  • Software: an additional building block to the PROCESS software stack that enables other communities to customize the publication of their data sets to their needs.
  • All this can be translated into a wide range of activities, from assessing innovation potential to performance prediction.