Big data promises and obstacles: Agricultural data ownership and privacy

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Abstract

The year 2022 marks the ten-year anniversary of the White House's Big Data Research and Development Initiative. While this initiative, and the others it spawned, helped to advance the many facets of data intensive research and discovery, obstacles and challenges still exist. If left unaddressed these obstacles will persist and at a minimum limit the potential of what can be achieved by harnessing the many new ways to collect, analyze, and share data and the insights that can be drawn from them. The opportunities and challenges related to Big Data in agriculture touch on all aspects of the general research data lifecycle; from instruments used to gather data, to advanced digital platforms used to store, analyze, and share data, and the innovative insights from using advanced computational methods. The eight papers included in this special issue were chosen in part because they highlight both the challenges and the opportunities that come from all stages of the data lifecycle common across agricultural research and development. These papers grew out of several workshops made possible by the support of the Midwest Regional Big Data Hub, which is sponsored by the National Science Foundation.

Original languageEnglish (US)
Pages (from-to)2619-2623
Number of pages5
JournalAgronomy Journal
Volume114
Issue number5
DOIs
StatePublished - Sep 1 2022

Bibliographical note

Funding Information:
Translating research results into actionable information must be practical whether the research is focused at the farm, county, state, national, or international level if we are to unlock the potential of the big data revolution. The focus of the three Big Data Big Ideas workshops that gave rise to the contributed papers in this special issue was just that–accelerate discovery into action. The importance of this work and the contributions included within this special issue cannot be overstated. The agricultural sector faces some unique challenges where data vary significantly in size and type and data generators represent a mix of public and private entities with different and sometimes conflicting requirements regarding the role of data privacy and ownership in research. Failing to address these challenges has real world consequences, which not only limit the potential of our research, but most importantly will impact the lives of millions of people who depend on advances that will make all parts of the food supply chain more efficient and robust to geopolitical strife and global environmental change. This special issue covers many of these challenges and in particular emphasizes the roles that data sharing and the development of trust among the many stakeholders involved in agricultural research play in a wide range of technical issues. Work in this area continues to advance through the efforts of the NSF sponsored Regional Big Data Innovation Hubs (BDHubs, n.d .) and is also moving forward through newer initiatives like the USDA‐NIFA and NSF Artificial Intelligence Research Institutes (National Science Foundation, n.d .). The challenges and solutions highlighted in this special issue provide a foundation for new ideas and future research that will take us beyond the hype‐cycle of the Big Data revolution and show us what can be achieved with the treasure trove of diverse data being collected today.

Funding Information:
In 2016, MBDH's Digital Agriculture Community member institutions, namely the University of North Dakota, University of Nebraska – Lincoln, Iowa State University, and Kansas State University, were awarded funding from the NSF Big Data Spokes program (National Science Foundation, 2016 ) in support of the Digital Agriculture: Unmanned Aircraft Systems, Plant Sciences, and Education (UASPSE) project (NSF award 1636865). In harmonization with the MBDH mission, UASPSE sought to develop Digital Agriculture partnerships that grow a Big Data literate workforce and drive innovation in the use of Big Data to help enable sustainable global food security. In addition to hosting online webinars such as Plant Phenomics Phridays and Metagenomics Mondays, project workforce development activities also included the promotion of MBDH sponsored workshops such as the 2018 Digital Agriculture Track of the Iowa State University Midwest Big Data Summer School.

Funding Information:
Translating research results into actionable information must be practical whether the research is focused at the farm, county, state, national, or international level if we are to unlock the potential of the big data revolution. The focus of the three Big Data Big Ideas workshops that gave rise to the contributed papers in this special issue was just that–accelerate discovery into action. The importance of this work and the contributions included within this special issue cannot be overstated. The agricultural sector faces some unique challenges where data vary significantly in size and type and data generators represent a mix of public and private entities with different and sometimes conflicting requirements regarding the role of data privacy and ownership in research. Failing to address these challenges has real world consequences, which not only limit the potential of our research, but most importantly will impact the lives of millions of people who depend on advances that will make all parts of the food supply chain more efficient and robust to geopolitical strife and global environmental change. This special issue covers many of these challenges and in particular emphasizes the roles that data sharing and the development of trust among the many stakeholders involved in agricultural research play in a wide range of technical issues. Work in this area continues to advance through the efforts of the NSF sponsored Regional Big Data Innovation Hubs (BDHubs, n.d.) and is also moving forward through newer initiatives like the USDA-NIFA and NSF Artificial Intelligence Research Institutes (National Science Foundation, n.d.). The challenges and solutions highlighted in this special issue provide a foundation for new ideas and future research that will take us beyond the hype-cycle of the Big Data revolution and show us what can be achieved with the treasure trove of diverse data being collected today. In response to the 2012 Big Data Initiative spearheaded by the U.S. Federal Government under President Obama (Weiss & Zgorski, 2012), the National Science Foundation (NSF) established four regional Big Data Innovation Hubs (BDHubs) in 2015 (National Science Foundation, 2015). Like the other three BDHubs (Northeast Big Data Hub, South Big Data Hub, and West Big Data Hub) the mission of the Midwest Big Data Hub (MBDH) has been “to strengthen the data ecosystem by developing effective networks across academia, industry, government, and nongovernmental organizations. The Hub strives to address scientific and societal issues of regional and national interest and to foster innovation across a number of priority and cross-cutting areas important in the Midwest (Midwest Big Data Hub, n.d.).” To this end, MBDH has cultivated Big Data communities in the Priority Areas of Advanced Materials Manufacturing, Smart & Resilient Communities (rural communities), Health, Water Quality, and Digital Agriculture (Midwest Big Data Hub, n.d.). New data generators, data platforms, and analytical methods make the promises of Big Data as relevant as ever. Data intensive agricultural R&D is raising ownership and privacy concerns, especially by private stakeholders. Sustained agricultural innovation requires a pipeline of new solutions to address data ownership and privacy issues. In 2016, MBDH's Digital Agriculture Community member institutions, namely the University of North Dakota, University of Nebraska – Lincoln, Iowa State University, and Kansas State University, were awarded funding from the NSF Big Data Spokes program (National Science Foundation, 2016) in support of the Digital Agriculture: Unmanned Aircraft Systems, Plant Sciences, and Education (UASPSE) project (NSF award 1636865). In harmonization with the MBDH mission, UASPSE sought to develop Digital Agriculture partnerships that grow a Big Data literate workforce and drive innovation in the use of Big Data to help enable sustainable global food security. In addition to hosting online webinars such as Plant Phenomics Phridays and Metagenomics Mondays, project workforce development activities also included the promotion of MBDH sponsored workshops such as the 2018 Digital Agriculture Track of the Iowa State University Midwest Big Data Summer School. The Unmanned Aircraft Systems, Plant Sciences, and Education project, in collaboration with Arrell Food Institute, convened two Big Data Big Ideas workshops with the aim of developing these cross-border Big Data agriculture partnerships. The first of these workshops was held at the University of Guelph in Guelph, ON, Canada in June 2019 in connection with the Agri-Food Excellence Symposium. A second Big Data Big Ideas workshop was held in September 2019 in partnership with Grand Farm (Grand Farm, n.d.) at the Microsoft Business Center in Fargo, ND, USA. These workshops touched on a number of topics including (but not limited to) advanced animal systems, agricultural supply chains, water quality in the context of field drainage systems, and farm data privacy. A third workshop, convened by University of North Dakota and the University of Minnesota, was held in June 2020, specifically focused on the topic of Big Data Promises and Obstacles: Agricultural Data Ownership and Privacy (BDPO) (Digital Agriculture Virtual Workshop, 2020). The papers presented in this special issue of Agronomy Journal are an outgrowth of that BDPO workshop.

Publisher Copyright:
© 2022 The Authors. Agronomy Journal published by Wiley Periodicals LLC on behalf of American Society of Agronomy.

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