The Replication Tax: Shifting the Financial Burden to Incentivize Reproducibility in Computational Research

R. Nagler and D. Bruhwiler
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Despite the innate reproducibility of software, computational science continues to struggle with reproducibility. The GSI mandate to establish best practices for computational reproducibility in high-performance geospatial software is a platform to change the behavior of computational scientists. We propose an economic approach: a “replication tax” on all publications in high-performance geospatial science. The easier it is to replicate research results, the less it costs authors to demonstrate their results are replicable.


  1. Yin D, Liu Y, Padmanabhan A, Terstriep J, Rush J, Wang S. A cybergis-jupyter framework for geospatial analytics at scale. PEARC 2017, Vol. Part F128771, a18, DOI: 10.1145/3093338.3093378e
  2. Geospatial Software: Connecting Big Data with Geospatial Discovery and Innovation
  3. Artifact Review and Badging Publication Policy of the ACM
  4. Article Structure: Material and Methods in Guide for Authors of Elsevier
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