| NSF Org: |
TI Translational Impacts |
| Recipient: |
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| Initial Amendment Date: | August 25, 2023 |
| Latest Amendment Date: | May 3, 2024 |
| Award Number: | 2303651 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Peter Atherton
patherto@nsf.gov (703)292-8772 TI Translational Impacts TIP Directorate for Technology, Innovation, and Partnerships |
| Start Date: | September 1, 2023 |
| End Date: | August 31, 2026 (Estimated) |
| Total Intended Award Amount: | $1,499,987.00 |
| Total Awarded Amount to Date: | $1,566,354.00 |
| Funds Obligated to Date: |
FY 2024 = $66,367.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
2601 WOLF VILLAGE WAY RALEIGH NC US 27695-0001 (919)515-2444 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
2601 WOLF VILLAGE WAY RALEIGH NC US 27607 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | POSE |
| Primary Program Source: |
01002425DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.084 |
ABSTRACT
Software that helps create insights from location-based information (geospatial data) is essential for addressing problems in many fields of national and societal importance, including public health, natural resources, urban planning, and disaster recovery. This project aims to expand and support the community of people developing and using a freely available geospatial software platform called GRASS GIS. For decades, GRASS GIS has allowed researchers around the world to find new solutions to pressing problems, and build on each other's work, by creating and modifying geospatial workflows for a wide range of analyses. The demand for GRASS GIS is increasing and therefore a coordinated effort is needed to grow the number of researchers and other software users at universities, government agencies, and businesses who can help maintain, and improve access to, GRASS GIS. This coordinated effort will make GRASS GIS more sustainable for supporting research with open-source software-by modernizing and expanding software distribution, simplifying how GRASS GIS can be used with other open-source software, improving quality assurance and software security, and accelerating the pace of important updates.
The goal of this project is to modernize software infrastructure and strategically grow the GRASS community to achieve a technologically and socially sustainable open-source ecosystem that provides scientists a foundation for novel, interdisciplinary research that will be accessible, reproducible, and ready for further innovations. The project aims to facilitate the adoption of GRASS GIS as a key geoprocessing engine by a growing number of researchers and geospatial practitioners in academia, governments, and industry. To achieve a technologically sustainable ecosystem with broader access to GRASS algorithms and models, the project will modernize and expand software distribution, increase security and quality assurance, and simplify maintenance of GRASS integrations with other software (such as R and QGIS). Streamlined contributor onboarding procedures and both remote and in-person training, mentoring, and promotion activities will encourage researchers to contribute new geospatial algorithms and models. Onboarding and teaching materials that are integrated in automated testing will significantly lower the costs to the developer community for maintaining this sophisticated software environment. The project aims to grow the community of GRASS users, contributors, and developers worldwide through engagement activities such as cross-project meetups, developer summits, community sprints, online and in-person training and one-on-one contributor mentoring. International involvement and diversity in project governance will be addressed by working with the GRASS Project Steering Committee to establish focused work groups that will implement policies ensuring an inclusive environment and high-quality contributions. Expanding the number and diversity of contributors from academia and research, non-profits, and industry will facilitate development of new geoprocessing engine features and ensure long-term maintenance of contributed research models. It will also enable faster development of geoprocessing tools to address major societal challenges linked to a location and place.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Please report errors in award information by writing to: awardsearch@nsf.gov.
