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Unlike traditional models of science that produce articles locked behind a journal paywall, open science is about opening up the tools, processes, and products of science to make research more reproducible and equitable. Whether you are interested in sharing a preprint on bioRxiv, accessing research data from a public repository, sharing your RNASeq protocols on protocols.io, or getting credit for your analysis code, there are many ways to engage with open science.
This interactive, hands-on class will cover some of the most prevalent trends in open science including open access publishing, open research data, open protocols, and open code. We will introduce emerging biomedical funder and publisher requirements for open science, describe how you can get credit and citations for your work, and share best practices for integrating open science practices into your research workflow. Through a series of short activities you will also have a chance to explore some of the most relevant open science tools for your research.
By the end of this workshop, learners will be able to:
Describe the different practices associated with open science/open research
Identify an open science practice to adopt in their own work
Ariel Deardorff is the Data Services Librarian at UCSF, and member of the Library's Data Science Initiative team. Ariel teaches courses on data management, open science and reproducibility. Contact Ariel at firstname.lastname@example.org or visit the Data Science Initiative Website.
Anneliese Taylor is an advocate for open access publishing and open research practices who is passionate about making open the default. She is the Head of Scholarly Communication at the UCSF Library, where she provides guidance and clarity to UCSF students, faculty, and staff on open access, scholarly publishing and research analytics.
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