Overview

Join us as we launch the fall Workshop series on Reproducibility for Biomedical Researchers! This session will start with an overview of the reproducibility "crisis" and highlight solutions for making research more reproducible. We will then hear from a panel of UCSF and Bay Area researchers about how they work to improve reproducibility in their work. Finally, we will conclude with a reception giving you a chance to connect with UCSF colleagues over food and drink! Please register below.

Learning Objectives 

By the end of this session, learners will be able to:

• Define reproducibility in the context of the biomedical sciences
• Describe two causes of non-reproducible research
• Identify one practice or tool to improve the reproducibility of their work

Instructor: Ariel Deardorff - UCSF Library Data Science Initiative

Panelists:

• Stephen Floor, PhD - UCSF 
• Byron Smith, PhD - Gladstone
• Seemay Chou, PhD - UCSF
• Perrine Janiaud, PhD - Stanford 

Speaker Bio

Ariel Deardorff is the UCSF Data Services Librarian and member of the Library’s Data Science Team. She teaches classes and does research on data management, open science, and reproducibility in the health sciences. She has a Master’s degree from the University of British Columbia and was a National Library of Medicine Associate Fellow before arriving at UCSF.

This workshop is part of a series on Biomedical Reproducibility. Other workshops in this series include:

• Sept 19 – Introduction to Reproducibility, Researcher Panel + Reception! - Ariel Deardorff
• Sept 26 – Rigorous Experimental Design – Karla Lindquist, PhD
• Oct 3 – Open Publishing - Veronique Kiermer, PhD, and Dan Morgan
• Oct 10 – Open Protocols – Lenny Teytelman, PhD
• Oct 24 – Open Code – Karthik Ram, PhD
• Oct 31 – Peer Review – Jessica Polka, PhD
• Nov 7 – Data Publishing – Daniella Lowenberg
• Nov 14 – Building a Reproducible Lab – Elizabeth Silva, PhD