Cooperative Extension, which serves the role of application and outreach, is a “successful model for scientific discovery to be transferred to the end user is through the continuum between campus based faculty and cooperative extension specialists”. A number of cooperative extension specialists are researchers within the CAES. Another component of the land grant university is the Agricultural Experiment Station. The mission of the Agricultural Experiment Station at the University of California, Davis is to “conduct research that encompasses the continuum of fundamental and applied research for the purpose of developing new knowledge and technologies that address specific problems of importance to the people of California. Key to this mission is a broad range of research focused on the discovery of solutions and the development of educational programs that disseminate knowledge and technology to an identified clientele. The AES mission focuses on agricultural, environmental and societal issues that are impacted by, or impact upon, the management of agricultural and natural resource systems”.The data come from 12 interviews with agricultural researchers at UC Davis. To obtain our sample, we first identified 107 research staff and faculty whose work was described on their individual or departmental websites as agriculture related. The pool of 107 research staff and faculty included researchers from 18 departments: the 15 current departments in the College of Agriculture and Environmental Science4 , as well as the departments of Civil and Environmental Engineering, Chicano/a Studies,square plastic pot and Native American Studies, and an interdisciplinary center on campus housed in the UC College of Agriculture and Natural Resources.

We also consulted a panel of subject librarians who work with UC Davis agricultural scholars to ensure our sample reflected the diversity of types of agricultural research at UC Davis. From the list of 107 researchers, we sent invitations to 43 researchers representing 16 of the departments, all position types and career stages. This was a purposive sample designed to capture the range of agricultural research at UC Davis and to represent the University’s notable research areas, such as viticulture and enology, ecology, genomics, and plant microbiology. From the initial sample of 43 researchers, we received 13 positive responses and were able to schedule 12 interviews within the study’s time frame. The final sample of 12 included 5 tenured faculty, 3 pre-tenured faculty, 2 research staff and 2 Cooperative Extension specialists, representing 10 different departments. The interviews were conducted in researchers’ offices. The session length varied from 21 minutes to 1 hour and 25 minutes, with an average length of 48:15; all were recorded with permission from the interviewee. The interviewers used a semi-structured interview protocol, wherein 11 questions served as an outline for the interviews5 . Additional questions were asked to probe for greater detail or clarify researchers’ responses. Interview recordings were transcribed and anonymized to remove names and identifying information. The research team analyzed the interviews using a system of open coding and focused coding. First, all transcripts were coded to identify important topics and themes that emerged within the interviews. Using the code lists developed through open coding, the research team organized a focused code list and re-coded all 12 interviews to standardize the results. We identified five themes as integral to agricultural research at UC Davis: a diverse, interdisciplinary research agenda; research data management; scholarly communication; aspects of collaboration at UC Davis; and research challenges.

We then clustered the codes according to these thematic areas. Using the qualitative analysis software Dedoose, we analyzed the code clusters to develop our findings. Our report also includes a discussion of the implications of our findings for library services. Researchers described several important types of challenges that the library’s research support services may be able to address, and these opportunities are considered in the conclusion. Our findings should not be interpreted as a generalization about all agricultural researchers at UC Davis. It is to be noted that the methodology has important limitations: the sample is purposive rather than random, and offers a relatively small N, characteristics which preclude any conclusions about statistical significance. Instead, the findings are intended to offer guidance to the reader by providing an increased understanding of the challenges that agricultural researchers at UC Davis face that may inform improvements to support and services for agricultural researchers. While not suited to statistical generalization, qualitative methods such as interviews offer more detailed information about how people understand their work, social groups, and societal context. This type of information is more useful for the purposes of our research than statistical conclusions would be. The UC Davis College of Agriculture and Environmental Sciences is a global leader that “produces a better world, healthier lives, and an improved standard of living for everyone by addressing critical issues related to agriculture, food systems, the environment and human and social sciences”6 through research, education, and outreach. UC Davis is ranked the #1 university in the world for teaching and research in agriculture and forestry7 . Agricultural research at UC Davis covers many disciplines and research topics. The scholars interviewed for this study research environmental toxicology, genomics, bio-informatics, plant physiology, plant virology, plant interactions with microbes and insects, community ecology, food science, local and regional food systems, nutrition, soil science, agronomy, horticulture, animal science, enology and viticulture, and agricultural economics. Agriculture research integrates multiple fields of study. In the field of environmental toxicology, researchers look at the effects of toxins on humans, food crops, and the environment. One interviewee studies the effects of pesticides in the food supply.

The research has implications for environmental health and public health particularly for medical diseases such as cancer and is of interest to both producers and consumers of agricultural products. Another looks at biological components of natural plants particularly in commodity crops to study food function. The plant scientists in our study look at better ways to grow crops. For example, one scientist studies crop uptake of carbon dioxide, which impacts crop yield and water use, and another assesses the potential for environmentally sound management practices to decrease the impact of diseases on crop production. Another research approach is community ecology, wherein interactions between plants, microbes and insects are studied to examine soil microbial communities’ impact on plant defense and pest insects. At UC Davis, plant sciences and plant biology are two distinct departments in two different colleges. CAES has a Department of Plant Sciences which encompasses research from “lab to field, to forest, range land, and beyond”8 that strives to meet global agricultural, ecological and environmental needs. The College of Biological Sciences has a Department of Plant Biology that studies plants as organisms including plant molecular and cellular biology,25 liter pot plant physiology and biophysics, and plant structural and developmental biology. Our study included two researchers from the CAES Department of Plant Sciences. Animal scientists study both domestic and wild animals in their respective environments. The animal scientist in our sample studies livestock nutrition and greenhouse gas emissions by livestock, thus contributing to research on sustainable animal agriculture. Agricultural researchers at UC Davis study a variety of plant and animal species including humans. Scientists draw on both lab and field methods, often in combination, to study agricultural systems from the molecular level to the ecosystem level. Molecular level research focuses on the study of genomes and genetics, or chemical compounds such as natural antioxidants, floral nectars, and scent compounds. Crop research pertains to commodity crops such as coffee beans, legumes, grapes, almonds, wheat, blueberries, strawberries, pistachios, sweet potatoes, roses and fruit and nut trees. Some research is done at the level of the community or system such as food systems research, community ecology research, and plant-microbial and plant-microbial-insect interactions. The microorganisms studied include both beneficial and pathogenic bacterial species as well as viruses. Much of the research involves lab and field experiments, and often, the researcher performs both.

This may reflect the applied nature of agriculture, in which lab research results are validated by field studies and explanations for field observations may be further studied and tested in the lab. The rate at which data is collected and stored is increasing exponentially from year to year. In 2014, presented that certain big-data analytics repositories exceeded exabytes. This figure is significantly smaller then what is seen today.stated in 2019 that 90% of the data in the world, at that point, was generated starting in 2017 and was then compounding at a rate of 2.5 quintillion bytes per day. Today, the practice of collecting vast quantities of data at an exceedingly fast rate has been adopted in just about every corner of the digital world and it is surely not going to waste. Big data has provided many benefits to society including modeling the spread of diseases, crime prediction and financial market analysis. However, two paramount problems with big data are the potential for data leakage and the question of who owns that data. Concern for the security and proper handling of data has been a heightening concern of both individuals and institutions. Stories covering unprecedented data leaks by large organizations, like Adobe in 2013 and a number of educational institutions since 2005, appear too regularly in the news. Worse than the unintentional leaks is the multitude of instances where sensitive data was voluntarily released or sold. A recent and well known example is the controversial 2018 case where 50 million Facebook users personal data was misused by Cambridge Analytica after Facebook sold it to them. Public awareness was raised by the Facebook scandal and other global publications leading to new and stricter data privacy laws around the world. Regarding agricultural data, however, observes, ”for some time now the issue of data misuse and controversy has been well known to farmers and the agricultural community.” Back in 2014, Monsanto, an American agrochemical and agricultural biotechnology corporation, left customers credit card information and other private data exposed on their servers. Another case similar to the 2018 Facebook case in that data was willfully exchanged was Haff Pultry v Tyson et al., in 2017. 38 chicken farmers raised a class action lawsuit against a number of chicken processing companies, including Tyson Foods Inc., ”for allegedly [selling] production data to 3rd parties” in order to keep their prices below competitive levels. These reoccurring instances of cooperate negligence and misuse of data are bound to increase the levels of mistrust the public holds toward cooperation’s holding their data.There has been a recent explosion of digital technologies in agriculture systems giving rise to the relatively new and booming field of precision agriculture. Precision agriculture, defined in, is ”the application of technologies and principles to manage spatial and temporal variability associated with all aspects of agricultural production for the purpose of improving crop performance and environmental quality.” Autonomous tractors, new genotypes, improvements to pest and weed management, and refined fertilizer use are just a few currently underdevelopment precision agriculture technologies. These technologies present the potential for an exciting future in agriculture, but successfully deploying them will require both the production and utilization of massive new stores of data. This use of data is especially due to the use of machine learning models in many cutting-edge technologies which require large data collections to train. A principal issue precipitating the unnecessarily large volume of data produced today is that much of it may not be discoverable, interpretable and/or reusable. Copious amounts of data are produced by agricultural research institutions but is most often stashed in private repositories due to the secure nature of the data. Furthermore, researchers may be unsure of what data will be useful resulting in data that is stored raw and unformatted and, therefore, ultimately unusable. My proposed research addresses the issue of discoverability in that its primary goal is to facilitate the sharing of secure data. I adopted an open-source software, built and designed by a community of farmers, known as FarmOS, which is a web interface for farmers to enter and maintain agricultural data and information. Furthermore, they have developed a custom data structure for maintaining the data which enables easy interpretation and is reusable for others who may use that data.