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The goal of the BSSw Fellowship program “is to foster and promote practices, processes, and tools to improve developer productivity and software sustainability of scientific codes”. The bulk of the applications process is a proposal for a one-year funded activity that promotes development or use of better scientific software. This year’s fellows’ projects focus on best practices for developing research software, reducing technical debt in scientific software, debugging and improving reliability in scientific appllications, and understanding social challenges in the evolution of scientific software products. The award is $25,000; applicants must be affiliated with a US-based institution that is eligible to receive DoE funds.
BSSw aims to “address pressing challenges in software productivity, quality, and sustainability.” It comprises multiple communities with connections to various fields of science and computing, with the over-arching goal of promoting awareness of good software practices in science.
Those who are not interested in applying to the fellowship program but who still want to consider contributing to BSSw can go here.
The Fall 2019 Meeting dates will be November 4th - 6th (MTW), where Monday and Tuesday will be full days, while Wednesday will likely be a half day. The location for this meeting is once more at LASP, specifically, in the LSTB building (Room A200 - note this is a different building/room than past meetings).
This link provides visitors to LASP with information on transportation to and from DIA, as well as around Boulder itself, helpful maps of the area, lodging, restaurants, etc.
Registration is required (so we can get a headcount for food), but free. The link to the meeting registration (as well as other pertinent information) can be found on the meeting’s main website.
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.