October 30th, 2013
The Universal streaming archive of the October 25, 2013 “Scientific Reproducibility: Opportunities and Challenges for Open Research Data and Code” presentation by Victoria Stodden is available for online viewing at the following URL:
Abstract: It is now widely recognized that the traditional published article is insufficient to permit verification of computational results. The emergence of powerful computational hardware combined with vast data collection and storage capabilities presents many novel opportunities for researchers. Unfortunately current standards for communication of published computational findings make verification and validation next to impossible. A movement toward reproducible research – dissemination that includes sufficient experimental details such that results can be replicated by others in the field, i.e. the code and the data – has developed in many disciplines and research areas to address this shortcoming in research communication. In this talk Dr. Stodden will explore the problem and address solutions emerging from researchers and institutions, federal policy efforts, and journal publication standards.
Bio: Victoria Stodden is an assistant professor of Statistics at Columbia University whose research centers on the multifaceted problem of enabling reproducibility in computational science. This includes studying adequacy and robustness in replicated results, designing and implementing validation systems, developing standards of openness for data and code sharing, and resolving legal and policy barriers to disseminating reproducible research. Her work has resulted in platforms and tools such as SparseLab, RunMyCode.org, and the Reproducible Research Standard. Stodden is a member of the National Science Foundation’s Advisory Committee on Cyberinfrastructure, the Mathematics and Physical Sciences Directorate Subcommittee on Support for the Statistical Sciences at NSF, the National Academies of Science committee on Responsible Science: Ensuring the Integrity of the Research Process, and several committees in the American Statistical Association. She completed her PhD in Statistics and her law degree at Stanford University, and her Erdös Number is 3.
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