Date: May 3, 2016
The Center for Urban Science + Progress
1 MetroTech Center, 19th Floor
Brooklyn, NY 11201
Achieving reproducibility in scientific research is a laudable goal, however this has been difficult to achieve. While data and data analysis play a central role in many scientific domains, most papers specify their methods and data only informally and omit important supplemental material. High quality journals have responded to this issue by making reproducibility a requirement for publication. Understanding the challenges to reproducibility and combating them with tools and best practices is therefore of cross-disciplinary relevance.
The Moore-Sloan Data Science Environment at NYU is pleased to announce a symposium on reproducibility that will be held on May 3, 2016.
At the NYU Reproducibility Symposium, we will showcase tools to help make the reproducibility process easy along with case studies showing how creating reproducible experiments has helped other research groups. The symposium will consist of keynotes and tutorial sessions in the morning, followed by discussions of research topics in reproducibility and hands-on sessions in the afternoon.
Please register for the Symposium via this non-binding registration form to help us in our planning!
- Juliana Freire, Professor of Computer Science and Engineering and Data Science; Executive Director, NYU Moore-Sloan Data Science Environment
- Dennis Shasha, Professor of Computer Science, Courant Institute of Mathematical Sciences, NYU
- Kyle Cranmer, Associate Professor of Physics, NYU College of Arts and Sciences
- Neil Beck, Professor of Politics, NYU College of Arts and Sciences
- Fernando Chirigati, PhD Student, NYU Tandon School of Engineering
- Remi Rampin, Research Engineer, NYU Tandon School of Engineering
- Margaret Smith, Physical Sciences Librarian, NYU Division of Libraries
- Vicky Steeves, Librarian for Research Data Management and Reproducibility, NYU Division of Libraries and the Center for Data Science