The National Institute of Standards and Technology (NIST) funded the multi-university five-year Center of Excellence for Risk-Based Community Resilience Planning (CoE), headquartered at Colorado State University, to develop the measurement science to support community resilience assessment. Measurement science is implemented on a platform called Interdependent Networked Community Resilience Modeling Environment (IN-CORE). On IN-CORE, users can run scientific analyses that model the impact of natural hazards and resiliency against the impact on communities. The IN-CORE platform is built on a Kubernetes cluster with Docker container technology.
Here are two simple steps to quickly get you up and running with IN-CORE:
conda config --add channels conda-forge
conda install -c in-core pyincore
Gain a comprehensive understanding of IN-CORE by reviewing the step-by-step manual. To delve deeper into advanced IN-CORE topics, check out our detailed tutorials.
Got questions or need assistance? There are three ways to reach out for help review our: FAQs for the most common questions, join the IN-CORE Slack channel, or email our dev team.