Reproducible Research in Computational Harmonic Analysis

TLDR

Scientific computation is central to modern science but is error‑prone and inadequately vetted, creating a crisis that reproducible computational research seeks to address. The article reviews the authors’ reproducible research approach, its evolution, and the arguments for and against it. They publish papers together with the complete computational environment that reproduces the results, integrating this practice into research and graduate training. Over 15 years, the authors have practiced reproducible research and incorporated it into their scientific work and graduate training.

Abstract

Scientific computation is emerging as absolutely central to the scientific method. Unfortunately, it's error-prone and currently immature—traditional scientific publication is incapable of finding and rooting out errors in scientific computation—which must be recognized as a crisis. An important recent development and a necessary response to the crisis is reproducible computational research in which researchers publish the article along with the full computational environment that produces the results. The authors have practiced reproducible computational research for 15 years and have integrated it with their scientific research and with doctoral and postdoctoral education. In this article, they review their approach and how it has evolved over time, discussing the arguments for and against working reproducibly.