Overview

Most modern advances in science have been made possible thanks to use of software. This software, also known as “research software”, has become essential to progress in science and engineering. Data and publications most often created, analyzed, and stored electronically, using tools and methods expressed in software. Despite the importance of research software for science, a majority of scientists do not have sufficient training and understanding of best practices that allow for reuse and reproducibility of software artifacts. 

In this workshop you will learn how to set up you work so others can easily reproduce all of your computational steps and generate outputs in a variety of formats. You’ll also learn about best practices for sharing code, when to turn a loose collection of scripts into a software package, and how to get academic credit for such work. Please register below.

Learning Objectives 

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

• Explain several ways in which to share their work as reproducible notebooks.
• Share and archive code/software associated with papers

Instructor: Karthik Ram, PhD - Berkeley Institute of Data Science, rOpenSci

Instructor Bio

Karthik is a senior research data scientist at the Berkeley Institute of Data Science and a co-founder and director of the rOpenSci project, and The US Research Software Sustainability Institute. Karthik is also a senior PI at the UC Berkeley Initiative for Global Change Biology. Prior to joining Berkeley, he earned his PhD in Ecology & Evolution from the University of California, Davis. Much of his recent work focuses on building tools and services around open data and growing diverse data science communities.

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