Open science is the movement to make scientific research, data, and dissemination accessible to all levels of an inquiring society. Practicing open science means practicing research in a way that enables others to collaborate and contribute, and ensuring that research data, lab notebooks, research processes, and published results are properly documented and openly shared to enable reuse, redistribution, and reproduction.
Below we provide key resources in four fundamental areas of open science, with a particular emphasis on resources relevant to the UCSF community. This content is built from the Library’s Open Science 101 class.
Open access (OA) is a publishing model whereby scholarly journals, articles, and books are published online with no access restrictions immediately upon publication, and with little to no restrictions on reuse of the material. See What is Open Access?
- Green OA - sharing an approved version of an article in open repository
- UC’s OA policies
- UC’s eScholarship open publishing platform
- NIH Public Access Policy
- Preprint resources
- Gold OA - open license, on publisher platform, sometimes requiring payment
- Evaluating publishers
- OA article discounts for UCSF and all UC authors
- UCSF OA Fund
Open data is the practice of sharing the research data underlying the findings of your publications in a public data repository.
Open methods is the practice of sharing your research methods on open platforms to improve reproducibility, share knowledge, and get credit.
- Details about UC’s protocols.io pilot
- Other methods and protocols resources (some closed)
- How to create a new protocol from protocols.io
- How to write an easily reproducible protocol from AJE
- Clinical trial protocol development from UCSF’s Clinical Research Resource HUB
- Systematic review protocol templates and checklists from Cornell University Library
- AsPredicted and OSF Registries for pre-registering research studies
Open code is the practice of making your software code openly available to improve transparency and re-use
- Open code class taught by Karthik Ram from ROpenSci
- Good Enough Practices in Scientific Computing
- Github’s guide to Making your code citable
- The Turing Way - A guide to reproducible data science
- UC Open Source Software Resources