Access to open data, open software and open results is important for transparency and supports reproducibility of research findings. It is critical to supporting disaster emergency responses all over the world, to advancing the response to the global pandemic, to advancing science in response to big and small questions, and making science more inclusive, impactful, and focused on the public good.

This course is designed to introduce researchers to the practices, characteristics, and benefits of open data, open software, and open results via the researcher workflow and research life-cycle. This course is an opportunity to review key practices that support preservation, sharing, using, and attribution of open data, software, and other results to advance science.

Participants will be able to articulate the definitions and characteristics of open data as well as the concepts of metadata, primary, and secondary data. They will be able to identify open software practices and resources for sharing, use, maintaining, and evolving open software while using open software to streamline workflow. Participants will be able to explain how, when, and where to make research outputs open and accessible while discussing the challenges and benefits of open results practices. Finally, participants will be able to create a plan to implement open research in their contexts.

If taken with Practicing Open Science: The principles, ecosystem, and tools, participants will gain a broad overview of open science and how to practice it with immediately applicable actions.