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Victoria Stodden
Associate Professor

Victoria Stodden
Enabling reproducibility in computational science, including the study of 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.

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CIRSS Publications

Chard, K., Gaffney, N., Jones, M. B., Kowalik, K., Ludäscher, B., Nabrzyski, J., ... & Willis, C. (2019, June). Implementing computational reproducibility in the Whole Tale environment. In Proceedings of the 2nd International Workshop on Practical Reproducible Evaluation of Computer Systems (pp. 17-22). Read more

Brinckman, A., Chard, K., Gaffney, N., Hategan, M., Jones, M. B., Kowalik, K., ... & Stodden, V. (2019). Computing environments for reproducibility: Capturing the “Whole Tale”. Future Generation Computer Systems, 94, 854-867. Read more

CIRSS Projects

The Whole Tale: Merging Science and Cyberinfrastructure Pathways
Bertram Ludaescher, PI (Illinois); Kyle Chard, co-PI (U of Chicago); Victoria Stodden, co-PI (Illinois); Matthew Turk, co-PI (Illinois); Niall Gaffney, co-PI (Texas Advanced Computing Center)
Funding Agency: NSF - CC*DNI DIBBS

CIRSS News

September 24, 2019
iSchool researchers present at ro2019
CIRSS researchers will present their work at the Workshop on Research Objects 2019 (ro2019), which will be held in conjunction with eScience 2019 on September 24-27 in San Diego, California. The Research Objects approach proposes a way to "package, d…

Past CIRSS Events

September 13, 2019
Advancing Data-enabled Discovery by Enabling Reproducibility and Transparency
In this talk I will give an overview of recent developments including the 2019 National Academies of Science, Engineering, and Medicine consensus report "Reproducibility and Replication in Science" (I…

September 2, 2016
Introduction to the Whole Tale Project
PI's Bertram Ludäscher, Matt Turk and Victoria Stodden will present an introduction to the Whole Tale project, a five-year project newly funded by the NSF CC*DNI DIBBS program.  The goal of the …

October 14, 2015
Large scale data analysis: Simpson's paradox, data integrity, and reproducibility.
Abstract:We consider factors that can give rise to unreliable or unstable outcomes in empirical research. For example, seemingly small differences in data preparation, consideration of outliers and mi…

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