Biosecurity Commons will be the world’s first Biosecurity virtual lab for use in research and decision-making. It will empower decision makers and researchers with cloud-based modelling solutions to respond to current and emerging biosecurity threats.
The Biosecurity Commons will address the shortcomings of Australia’s biosecurity modelling capability, which is a dispersed network of diagnostics, analytics and intelligence. The project will improve access to computing resources, licensing, IT expertise, and address issues such as IP (Intellectual Property) concerns, and silos between jurisdictions and sectors. This will remove barriers in the existing framework where biosecurity models are often inaccessible and frequently developed for a single purpose, based on a single pest or disease, and are rarely re-used or shared.
Biosecurity Commons will deliver tools that support planning and preparation to ensure timely and effective responses to biosecurity events, and will allow researchers and decision-makers to investigate a wide range of questions related to biosecurity risk and response. The platform will allow jurisdictions to share analytics and modelling to demonstrate that the right decisions are being made; and to improve modelling research by working collaboratively.
The Biosecurity Commons project leverages the existing EcoCommons platform architecture and components, which offers a suite of common approaches for building analytical modelling outputs, as well as integrating a vast array of geospatial data. The project will build a permissioned online environment for working securely, that will promote collaboration across state jurisdictions and disciplines of biosecurity research.
Visit Biosecurity Commons.
Who is this project for?
- Research organisations
- Government policy makers (state and commonwealth)
What does this project enable?
For the first time, researchers, government and practitioners across organisations will be able to securely share biosecurity data, and reproducible models and analytics. This will build trust, transparency and confidence in model outputs, and accelerate research through the reuse and repurposing of existing models.