COVID-19: Automated Scientific Knowledge Extraction for Data-Driven Policy
In partnership with DARPA’s ASKE and World Modelers programs, this project aims to produce reliable insights for state and local decision makers regarding the COVID-19 pandemic.
Augmenting Human Intelligence for Crisis Response
Traditional modeling and data analysis can be a slow, bespoke, and error prone process. Galois has been working with DARPA to improve the agility, speed, and confidence of data and model analysis for crisis response, to allow domain experts to inform their decisions, policy, and actions with machine intelligence and automated reasoning.
The COVID-19 Pandemic
As part of this effort, Galois engineers and scientists are analyzing the data and models emerging from the COVID-19 pandemic. We are leveraging a novel pipeline and toolset to produce cleaned data sets, model analysis, and other resources for the federal, state, and local governments; the scientific community; and other friends and colleagues working on this crisis.
ASKE & World Modelers
These programs have been advancing the state of the art to automate some of the manual processes of scientific knowledge discovery, curation and application; and then to leverage this extracted to knowledge in the form of data and models to enable rapid response to emerging crises, allowing policy makers to drive decisions with data and models, deriving insight in days or hours instead of months or weeks.
Licensing and Collaboration
Galois is releasing all data, models, and resources under the MIT open source license to encourage collaboration.
Our COVID-19 pipeline and tool set are in active development. We would love feedback on how to make our resources better, and directly apply our technologies to important problems facing state and local policy makers. Please contact the team if you have any questions or comments.
Data, Models and Resources
Stay tuned for updates to our Github page for the COVID-19 pandemic for a list of published models and data.