Location: Cotton Ginning Research
Project Number: 3050-41000-010-074-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Jul 15, 2019
End Date: Jul 14, 2024
Cooperator will: Objective 1 – Provide day-to-day coordination, GIS analytical support, and programming support on PDI approved jobs focused on developing digital tools to support agricultural researchers and stakeholders. Objective 2 - Illustrate the utility and benefits of the “Data Innovations” developed by PDI through multiple venues including an annual PDI “Showcase” outreach event, journal publications (at least one), presentations at scientific conferences (e.g., ASABE, ASA/SSSA, AGU), and ARS (e.g., Harvest articles, social media, Inform and Engage webinars), and university partners’ (e.g., YouTube video, social media, Extension workshops) content platforms. Objective 3 – Develop success metrics for USDA-ARS PDI and a suite of digital tools (e.g., dashboards, insights, story maps) for various audiences (e.g., ARS leadership, researchers, stakeholders). Objective 4 – Work with the USDA-ARS PDI Director of Operations to develop quarterly and final project reports. All reports will include individual project summaries and financial accounting details.
The primary component of this agreement requires CSU to hire full-time GIS analysists, full-time project coordinators, a Ph.D. student, and/or several part-time computer science undergraduate student employees to work with the PDI leadership team and PDI project coordinators, GIS analysts, software developers, Postdocs, and undergraduate students hired under other university agreements to complete the various PDI projects/jobs/tasks managed by the PDI leadership team in support of PDI goals listed below. The objectives will involve collaborative PDI work to support the following PDI goals: 1) Prioritizing creation of data solutions and tools for USDA cotton research and the Long-Term Agroecosystem Research Network; 2) Developing national USDA cybersecurity approved secure, automated data collection systems for continuous monitoring systems (e.g., meteorology, stream flow) to include data transmission, QA/QC, storing data in ESRI/Microsoft Azure computing platforms, and troubleshooting tools; 3) Developing digital infrastructure for automated and optimized high-throughput analytical laboratory prototypes for common soil, water, manure, and plant analysis; 4) Developing a universal sample tracking system for agricultural research, available to USDA-ARS and collaborators; 5) Working with the USDA Office of the Chief Information Officer to develop USDA UAS and UGS policies, department regulations, list of approved USDA UAS, enhanced UAS and UGS software tools, and USDA approved cybersecure cloud-based integrated platforms for UAS and UGS; 6) Standardizing and integrating agricultural research data into the USDA-ARS PDI commercial Azure cloud environment, including the integration of existing ARS databases (e.g., GraceNet, STEWARDS, LTAR); 7) Developing customized digital laboratory and field notebooks using Esri apps (e.g., Survey123, Field Maps) that store collected data in the USDA-ARS AGOL or USDA-ARS PDI Azure cloud environments, to transform USDA-ARS from a paper-based to a digital data collection research organization; 8) Develop data visualization tools (e.g., dashboards, insights, story maps) for data stored in the USDA-ARS AGOL or USDA-ARS PDI Azure cloud environments; 9) Expanding the USDA-ARS PDI uniform terminology data dictionaries to include new research terms and align with national and international ontology and data shape systems through the PDI partnership with the National Agricultural Library; 10) Expanding the protocols.io platform for aligning standard operating procedures across the agricultural research community and bring this platform into the USDA-ARS PDI Authority to Operate; 11) Working with ARS researchers to upgrade ARS software to be hosted in a USDA cloud environment with an Authority to Operate and to achieved compliance with current USDA cybersecurity guidelines; 12) Linking external data sources (e.g., NOAA, USGS) to the USDA-ARS PDI cloud platform to create a one-stop-shop for agricultural researchers; 13) Developing a Decision Support Informatics platform for agricultural research information (e.g., data dashboards, decisions support tools, models) for farmers, ranchers, and agricultural processors.