The Need for a Digital Agriculture Community
Land owners, producers, agribusinesses, government, and other entities have access to increasingly large and complex arrays of spatiotemporal information about land and agriculture, derived from real-time sensor data streams, aerial imagery, survey data, and predications from management and policy simulation models.
With the growing volumes of data, the potential is vast for improved understanding of plant and animal food systems and their potential impact on the economy, environment, and society more broadly. The data also offer the potential to address the challenging array of forces in agroecosystems, such as balancing productivity and sustainability and developing robust responses to increasing uncertainty under global climate change.
While the potential is great, our ability to leverage these resources is constrained by lack of 1) tools and resources to support appropriate integration and use of data, 2) a broader infrastructure for sharing and collaborating on data-driven projects, and 3) approaches to data ownership and policies to support confidentiality and proprietary information.
Purpose of the Digital Agriculture Community
We are creating a Digital Agriculture Community to help develop partnerships and resources that will address opportunities and challenges in digital agriculture across several broad topics.
- Precision agriculture – for example, high resolution information about crop fields, novel sensor development to measure environmental conditions and inform management
- Ecosystem management and services – for example, the nexus of water, energy, and arable land; energy, carbon, and nutrient cycling; water quality; and impacts of climate on crop and livestock production
- Biosciences – for example, predictive phenomics, synthetic biology, and systems biology
- Socio-economic impacts – for example, agricultural economics and producer-level decision making in relation to rural well-being, policy, and supplying energy and food
- Data-related issues in the agricultural ecosystem – for example, better integration of agricultural data streams, improved collaboration among data owners, and barriers to sharing data such as protecting propriety and confidential information
The Digital Agriculture Community will focus on a broad range of specific big data issues.
- Food and nutritional security
- Ensuring a productive, diverse, and resilient agroecosystem
- Enhancing net benefits from the coupled human biotic system
- Producing food, feed, fiber, biofuels, bioproducts, and ecosystem services
- Facilitating team science and ensuring integration of life sciences, physical sciences, social sciences, and engineering in a transdisciplinary system (i.e., Convergence)
- Enhancing the efficacy of public-private partnerships
- Achieving the high potential for scalability and globalization
- Ensuring public and private access to the accumulated data and knowledge
- Educating the individuals who make managerial decisions related to the agroecosystem, including land owners, policy makers, NGOs, and environmental groups
- Enhancing the educational and hands-on research opportunities for the next generation of agricultural and data scientists to collaborate, innovate, and address the issues related to agriculture
The Digital Agriculture Community will pursue specific activities to engage new partnerships while leveraging existing consortia and centers.
- Propose and develop cross-discipline and cross-institution partnerships
- Design regional meetings and workshops to develop a common understanding of big data and identify opportunities for new partnerships
- Engage relevant stakeholders to improve data sharing and access, facilitate team science, and establish new partnerships with government, nonprofit organizations, and industry
- Foster an environment for multiple educational opportunities and broad dissemination of scientific principles and information