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MIDAS Seminar

MIDAS Reproducibility Challenge Showcase

Chris BrooksAssistant Professor of Information – School of Information, University of Michigan

The Reproducibility Showcase features a series of online presentations and tutorials from May to August, 2020.  Presenters are selected from the MIDAS Reproducibility Challenge 2020.

A significant challenge across scientific fields is the reproducibility of research results, and third-party assessment of such reproducibility. The goal of the MIDAS Reproducibility Challenge is to highlight high-quality, reproducible work at the University of Michigan by collecting examples of best practices across diverse fields.  We received a large number of entries that illustrate wonderful work in the following areas:

    1. Theory – A definition of reproducibility and what aspects of reproducibility are critical in a particular domain or in general.
    2. Reproducing a Particular Study – Comprehensive record of parameters and code that allows for others to reproduce the results in a particular project.
    3. Generalizable Tools – A general platform for coding or running analyses that standardizes the methods for reproducible results across studies.
    4. Robustness – Metadata, tools and processes to improve the robustness of results to variations in data, computational hardware and software, and human decisions.
    5. Assessments of Reproducibility – Methods to test the consistency of results from multiple projects, such as meta-analysis or the provision of parameters that can be compared across studies.
    6. Reproducibility under Constraints – Sharing code and/or data to reproduce results without violating privacy or other restrictions.