Effective Practices in Computational Reproducibility Workshop

September 19, 2017, 12:00pm│Columbia University, Alfred Lerner Hall, Broadway Room
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Post-workshop material
Computational Reproducibility Workshop - Victoria Stodden - Code Ocean - Sept 19, 2017 from codeocean
GitHub example from hands-on session
Source codeWorking example
Further reproducibility reading
About the workshop
Computational analysis plays a central role in scientific research. Scientists, journals and funding organizations increasingly ask that published research include associated data and code. Sharing this information is becoming the norm among researchers, but it is not always clear why this is important or how to do so. How can researchers conduct computationally reproducible work simply and effectively?

The session will address these topics, and will be divided into two parts, a talk and a workshop. The talk, given by Professor Stodden, will discuss the replication crisis, different levels of reproducibility, and will suggest practical steps for achieving reusability and computational reproducibility. The workshop, conducted by Code Ocean staff in collaboration with Professor Stodden, will give participants the tools they need to publish their code online. This will involve examples from the Code Ocean website and also code and data authored by workshop participants. By the end of this workshop, participants will be able to publish their code online. Personal assistance and advice will be available to anyone who is interested. Please bring a laptop if you would like to participate in the workshop.
Speakers
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 
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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.
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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.
Speakers:
Simon Adar, CEO, Code Ocean
Sunil Gupta, Director of Product Innovation, IEEE