The Importance of Standards for Sharing of Computational Models and Data

Russell A. Poldrack, Franklin Feingold, Michael J. Frank, Padraig Gleeson, Gilles de Hollander, Quentin J.M. Huys, Bradley C. Love, Christopher J. Markiewicz, Rosalyn Moran, Petra Ritter, Timothy T. Rogers, Brandon M. Turner, Tal Yarkoni, Ming Zhan, Jonathan D. Cohen

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The target article by Lee et al. (in review) highlights the ways in which ongoing concerns about research reproducibility extend to model-based approaches in cognitive science. Whereas Lee et al. focus primarily on the importance of research practices to improve model robustness, we propose that the transparent sharing of model specifications, including their inputs and outputs, is also essential to improving the reproducibility of model-based analyses. We outline an ongoing effort (within the context of the Brain Imaging Data Structure community) to develop standards for the sharing of the structure of computational models and their outputs.

Original languageEnglish (US)
Pages (from-to)229-232
Number of pages4
JournalComputational Brain and Behavior
Volume2
Issue number3-4
DOIs
StatePublished - Dec 2019

All Science Journal Classification (ASJC) codes

  • Developmental and Educational Psychology
  • Neuropsychology and Physiological Psychology

Keywords

  • Computational models
  • Data sharing
  • Reproducibility
  • Standards

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