Supporting Platforms and Infrastructure for Open, Collaborative Science
Our open source science work aims to accelerate the pace of scientific progress. Part of that is making sure researchers have access to reliable information and sustainable open source infrastructure. We support platforms where researchers can quickly and openly disseminate methods, tools, preprints (draft scientific papers), and other research outputs. We also partner with organizations contributing to the infrastructure underlying open science and serving the needs of communities around the world.
Enabling Knowledge Discovery
We aim to reduce barriers to knowledge discovery and access. We support platforms, tools, and research to represent, summarize, and discover our collective biomedical knowledge. We believe that fostering a more open and interoperable knowledge infrastructure will help accelerate the pace of research.
We collaborate with Andrew McCallum and the Center for Data Science at UMass Amherst to accelerate science and medicine through research and development of novel approaches to knowledge representation and automated knowledge base construction. The goal of the Computable Knowledge project is to enable an intelligent and navigable map of scientific knowledge using a branch of artificial intelligence known as knowledge representation and reasoning.
The Computable Knowledge project will facilitate new ways for scientists to explore, navigate, and discover potential connections between millions of new and historical scientific research articles.
Open Research Data
Researchers and leaders from the Chan Zuckerberg Initiative, the Allen Institute for Artificial Intelligence, Georgetown University’s Center for Security and Emerging Technology, Microsoft Research, and the National Library of Medicine of the National Institutes of Health have assembled and released a dataset of preprints, clinical reports, and published research papers about COVID-19, SARS-CoV-2, and the coronavirus group.
The COVID-19 Open Research Dataset (CORD-19) includes machine-readable full text of tens of thousands of papers, and is updated daily as new insights are released. With these machine-readable resources accessible and available for data analysis, the data science community has the opportunity to apply recent advances in natural language processing to find answers to questions within, and connect insights across, this content in support of the ongoing fight against this infectious disease.
In addition, to promote reuse and reproducibility, we encourage the open sharing of research data through services such as Dryad, a data publishing platform.
Building Computational Capacity
We believe in a future in which everyone in the biomedical community has the skills to make use of computational methods and engage in open science practices. The Chan Zuckerberg Initiative is focused on accelerating science by providing researchers with the resources and tools needed to do their best work.
Essential Open Source Software for Science
Open source software is crucial to modern scientific research, advancing biology and medicine while providing reproducibility and transparency. Yet even the most widely-used research software often lacks dedicated funding. CZI’s Essential Open Source Software for Science program supports software maintenance, growth, development, and community engagement for critical open source tools.
Open Science Team
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Essential Open Source Software for Science (Cycle 4)
This RFA supports the maintenance, growth, development, and community engagement of open source software projects to help make the computational foundations of biological research more usable and robust.
- Cycle 1 - $5 Million
- Cycle 2 - $3.8 Million
- Cycle 3 - $3 Million
- Cycle 4 - $11.1 Million