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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Wisconsin-Madison |
| Country | United States |
| Start Date | Sep 01, 2022 |
| End Date | Feb 28, 2026 |
| Duration | 1,276 days |
| Number of Grantees | 3 |
| Roles | Former Principal Investigator; Principal Investigator; Former Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2223103 |
An award is made to provide support to a collaboration between researchers at the University of Wisconsin, Madison and the University of New Mexico for the Environmental Data Initiative (EDI), a comprehensive data repository and data management support organization for the environmental research community. EDI facilitates the publication, use and re-use of environmental data generated by publicly funded research projects.
Researchers from a wide range of disciplines use this rich resource to better understand historic contexts and local variations of complex environmental processes. EDI’s unfettered and unbiased data access and public training opportunities have a high potential to broaden participation in science. Use of data obtained from EDI is demonstrated by over half a million annual downloads and over 1300 journal publications.
The EDI data repository and curation services are optimized at the intersection of reducing the burden of data documentation and formatting efforts for the data publisher and providing the data user with highly Findable, Accessible, Interoperable, and Reusable (FAIR) data. EDI approaches the tension between these two axes of data publication with simple metadata authoring tools that automate the process as much as possible, clear online guidance documentation, and staff curators.
The repository infrastructure uses a Service Oriented Architecture (SOA) design pattern where external software clients may upload, search, and access data through a REST web-service Application Programmable Interface (API). This architecture and EDI’s data portal provide the ability for users to access the data manually or programmatically, thus accommodating advanced data science workflows.
The modular software design also allows for optimal maintenance and upgrade while providing exceptional availability of service. Support from this award will enable EDI to focus on core activities, including: (1) outreach (2) data curation training, (3) providing curation tools and services, (4) improving data discovery and reusability, while (5) maintaining software and hardware to ensure optimal functioning of the EDI data repository.
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.
University of Wisconsin-Madison
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