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A report by the National Academy of Sciences has issued new recommendations to improve confidence in science through enhancing Reproducibility and Replicability. Often used interchangeably, these two terms are defined precisely in the report. Reproducibility means obtaining consistent results through computation with the the same input data while replicability means obtaining consistent results across experiments with their own data.
The PyHC project is directly aligned with their recommendation of “investing in research and development of open-source, usable tools and infrastructure that support reproducibility for a broad range of studies across different domains in a seamless fashion.”
This recommendation further supports that of the recent NAS report on Open Source Software Policy Options for Earth and Space Sciences which recommended that the “NASA Science Mission Directorate should explicitly recognize the scientific value of open source software and incentivize its development and support, with the goal that open source science software becomes routine scientific practice.”
The study was produced by the Committee on Reproducibility and Replicability in Science and funded by the National Science Foundation and Alfred P. Sloan Foundation.
The NASA Heliophysics Data Environment Emphasis (HDEE) solicitation has been released and can provide funding for developing Python packages for heliophysics. The solicitation is available here. The due date for the step-1 proposal is April 18th which consists of a title, a team, as well as a short description of the project.
A tutorial and example gallery has been added to the website. It can be found at http://heliopython.org/gallery/generated/gallery/index.html.
The report on the first Python in Heliophysics Community Meeting has been published and is available here.