NumFOCUS Projects Receive NASA Grants
Over half of funding available received by NumFOCUS projects
Eight NumFOCUS projects have been awarded grants as part of NASA’s efforts to provide support to open source software, tools, libraries, and framework which are critical to the Science Mission Directorate’s (SMD) scientific objectives.
The following projects will be receiving funding during the three-year grant term:
- NumPy, pandas, SciPy, scikit-learn (joint proposal)
The OSTFL program which falls under the Research Opportunities in Space and Earth Sciences (ROSES), received applicants from a highly competitive pool of over 60 submissions from the open science community. In total, NumFOCUS projects were awarded over half of the funding available, further demonstrating how crucial NumFOCUS projects are to NASA and the scientific community as a whole.
Astropy — Sustaining the Astropy Project
Astropy’s funding will address community concerns by improving the robustness of its project’s infrastructure. This award will fund a set of tasks including a mix of project-wide infrastructure improvements, targeted work on specific areas of the code that require support, enhancements to the Astropy education materials to encourage community engagement and testing standards.
“This is a major milestone for the Project as a whole, and we all are very proud of what we have accomplished together. As our first grant from NASA, it is an enormous step towards making Astropy sustainable for the long haul. The funding will help us support, expand, and maintain the openly-developed ecosystem the astronomy community has come to rely on,” said Erik Tollerud of Astropy.
Matplotlib —Revamping Matplotlib for Modern Data Structures
Matplotlib’s grant proposal centered around their desire to execute revamping for modern data structures. With this funding, they will now staff full-time support and partial support for the Matplotlib Project Lead, allowing them to take on more complex projects while executing critical day-to-day maintenance tasks required to keep the project healthy.
They will split this grant equally between two primary activities: overhauling their internal data representation, supporting physical units, and general library maintenance and community development.
“This grant not only enables us to create more efficiency within the library’s day-to-day operations, but it will also support a major refactoring of how Matplotlib internally stores data. Users will benefit from our support of data with physical units and the ability to directly integrate with modern data structures such as xarray,” said Thomas Caswell of Matplotlib.
“This is the largest proposed change to the library in over a decade and would not be possible without developers being supported as a result of this grant,” continued Caswell.
NumPy, pandas, SciPy, and scikit-learn — Reinforcing the Foundations of Scientific Python
This collaboration will address key challenges in maintenance, as well as implement technical improvements with a focus on computational performance and tighter integration between them. Maintaining continuous integration (CI) and extending it to, e.g. new Python versions and more hardware platforms, is one of the most time-consuming activities for each project.
“NumPy, pandas, SciPy and scikit-learn have teamed up to improve their interoperability, performance, and portability to newer platforms and GPUs. Their expectation is for the whole scientific Python ecosystem and its millions of users to benefit from the work made possible by this award,” said Tyler Reddy, SciPy Release Manager.
“The joint initiative will aim to support open source community members who would not normally be able to contribute, with leaders from each of these projects providing guidance along the way. These mostly-volunteer projects are thrilled that NASA will help us launch into the future, and we hope to launch NASA and the broader open science community to amazing places with this cross-cutting effort,” continued Reddy.
SunPy— Strengthening the Foundations of the SunPy Ecosystem
The grant will address three targeted efforts to strengthen SunPy’s foundations. This includes ensuring robust support for the analysis of complex data from next-generation missions and simulations by improving the technical infrastructure maintenance of their core library and nurturing its ecosystem of affiliated packages.
Additionally, they will be augmenting science-enabling functionality in key areas relevant for newly available solar-physics data sets. They will also provide training and outreach to the solar-physics community on how to most effectively use and contribute to SunPy.
“The SunPy ecosystem supports solar-physics research through the sunpy core library and its affiliated packages, which are developed under open-source and open-development principles. To continue the successful expansion of this ecosystem, this funding will improve the technical infrastructure for maintenance, augment science-enabling functionality relevant for newly available solar-physics data sets, and provide training to the solar-physics community on how to use and contribute to SunPy,” said Albert Y. Shih, the Project’s Lead Developer.
Xarray — Enhancing Analysis of NASA Data with the Open-Source Python Xarray Library
This grant will significantly expand the use of Xarray for research using NASA data and sustain the development of the library through specific maintenance and outreach activities including expanding testing and geoscience-specific functionality while creating interactive documentation. Xarray will also begin hosting public “Xarray for NASA data” virtual office hours along with a regular online Xarray tutorial series.
“Ultimately the success of this project will be measured by increasing adoption of Xarray among scientists using NASA data for research. This is a transitional moment in which the scientific community can either be stymied by data management or empowered with enhanced open-source software tools such as Xarray. Our tasks will enable the SMD community to fully unlock Xarray’s potential for efficiently exploring petabyte-scale NASA data, accelerating scientific discoveries in this age of cloud-computing and big data,” said Scott Henderson, Deepak Cherian, Jessica Scheick, Anderson Banihirwe and Alan Snow of Xarray.
Congratulations to all of the NASA OSTFL grant recipients! We look forward to witnessing and supporting the progress and accomplishments that result from these awards.