Building a vision for reproducibility in the cyberinfrastructure ecosystem: Leveraging community efforts

Dylan Chapp, Victoria Stodden, Michela Taufer

Research output: Contribution to journalArticlepeer-review

Abstract

The scientific computing community has long taken a leadership role in understanding and assessing the relationship of reproducibility to cyberinfrastructure, ensuring that computational results-such as those from simulations-are "reproducible", that is, the same results are obtained when one re-uses the same input data, methods, software and analysis conditions. Starting almost a decade ago, the community has regularly published and advocated for advances in this area. In this article we trace this thinking and relate it to current national efforts, including the 2019 National Academies of Science, Engineering, and Medicine report on "Reproducibility and Replication in Science". To this end, this work considers high performance computing workflows that emphasize workflows combining traditional simulations (e.g. Molecular Dynamics simulations) with in situ analytics. We leverage an analysis of such workflows to (a) contextualize the 2019 National Academies of Science, Engineering, and Medicine report's recommendations in the HPC setting and (b) envision a path forward in the tradition of community driven approaches to reproducibility and the acceleration of science and discovery. The work also articulates avenues for future research at the intersection of transparency, reproducibility, and computational infrastructure that supports scientific discovery.

Original languageEnglish (US)
Pages (from-to)112-119
Number of pages8
JournalSupercomputing Frontiers and Innovations
Volume7
Issue number1
DOIs
StatePublished - Jan 1 2020

Keywords

  • High-performance computing
  • In situ analytics
  • Molecular dynamics
  • Replicability
  • Reproducibility
  • Transparency

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications
  • Computational Theory and Mathematics

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