Effective Practices in Computational Reproducibility Workshop

September 19, 2017│Columbia University, Alfred Lerner Hall, Broadway Room
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About this workshop
Science is becoming more and more digital, and computational analysis is playing a more central role in research. Scientists, journals and funding organizations demand that published research should include associated data and code. Sharing open source data in this way is becoming the norm among researchers, but it is not always clear why this is important or how to do this easily and in the best possible way. How can I conduct computational reproducibility to lend more authenticity and credibility to my research?

This session will be divided into two parts, a talk and a workshop. The first part will talk about different levels of reproducibility and suggest simple steps that any researcher can follow to achieve best practices in computational reproducibility and reuse. In the second part, a hands-on workshop will be given to practice reproducibility. An example code from a published article will be demonstrated using the Code Ocean platform. By the end of this workshop, participants will be able to publish their code online. Personal assistance and advice will be given for anyone who is interested. Please bring a laptop if you would like to participate in the workshop.
Simon Adar, CEO, Code Ocean
Sunil Gupta, Director of Product Innovation, IEEE
Victoria Stodden
Victoria Stodden joined the School of Information Sciences at the University of Illinois at Urbana-Champaign as an associate professor in Fall 2014. She is a leading figure in the area of reproducibility in computational science, exploring how can we better ensure the reliability and usefulness of scientific results in the face of increasingly sophisticated computational approaches to research. Her work addresses a wide range of topics, including standards of openness for data and code sharing, legal and policy barriers to disseminating reproducible research, robustness in replicated findings, cyberinfrastructure to enable reproducibility, and scientific publishing practices. Stodden co-chairs the NSF Advisory Committee for CyberInfrastructure and is a member of the NSF Directorate for Computer and Information Science and Engineering (CISE) Advisory Committee. She also serves on the National Academies Committee on Responsible Science: Ensuring the Integrity of the Research Process. 
Previously an assistant professor of statistics at Columbia University, Stodden taught courses in data science, reproducible research, and statistical theory and was affiliated with the Institute for Data Sciences and Engineering. She co-edited two books released in 2014 - Privacy, Big Data, and the Public Good: Frameworks for Engagement published by Cambridge University Press and Implementing Reproducible Research published by Taylor & Francis. Stodden earned both her PhD in statistics and her law degree from Stanford University. She also holds a master’s degree in economics from the University of British Columbia and a bachelor’s degree in economics from the University of Ottawa.
Simon Adar
Simon Adar is the founder and CEO of Code Ocean, a cloud-based computational reproducibility platform incubated at Cornell Tech. He was a Runway postdoc awardee at the Jacobs Technion-Cornell Institute and holds a PhD from Tel-Aviv University in the field of Hyperspectral image processing. Simon previously collaborated with the DLR - the German Space Agency on the European FP7 funded EO-MINERS project to detect environmental changes from airborne and spaceborne sensors.