Session 4: Reproducibility and confidential or proprietary data: can it be done?
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Abstract
What happens to reproducibility when data are confidential or proprietary? Many journals can only ask that detailed access procedures be provided in a ReadMe file, but what mechanisms could be used to conduct computational reproducibility checks on such data? Should authors temporarily share their data with the journal for the purposes of reproducibility verification, even if they are not part of the public data replication package? Is it feasible to use a network of "insiders" to run code provided as part of a data replication package to assess reproducibility? Could a "certified run" be used?
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Edited video of expert panel presentation and discussion originated via video conference.
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2023-12-13
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Labor Dynamics Institute
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Data Privacy; Confidentiality; Computational Research; Research practices; Reproducibility; Replicability; Data Management; Social Sciences
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Labor Dynamics Institute. (2023, January 21). CRRESS Session 4: Reproducibility and confidential or proprietary data: can it be done?. YouTube. https://www.youtube.com/watch?v=ChR_0_zmQwk
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video/moving image
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captions
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none
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Captions are available. Slides are present, they are of accessable contrast.