Jakku, Emma (author), Taylor, Bruce (author), Fleming, Aysha (author), Mason, Claire (author), Fielke, Simon (author), Sounness, Chris (author), and Thorburn, Peter (author)
Format:
Journal article
Publication Date:
2019-12
Published:
Netherlands: Elsevier
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 203 Document Number: D12272
13 pages, Advances in Smart Farming and Big Data applications have the potential to help agricultural industries meet productivity and sustainability challenges. However, these benefits are unlikely to be realised if the social implications of these technological innovations are not adequately considered by those who promote them. Big Data applications are intrinsically socio-technical; their development and deployment are a product of social interactions between people, institutional and regulatory settings, as well as the technology itself. This paper explores the socio-technical factors and conditions that influence the development of Smart Farming and Big Data applications, using a multi-level perspective on transitions combined with social practice theory. We conducted semi-structured interviews with 26 Australian grain farmers and industry stakeholders to elicit their perspectives on benefits and risks of these changes. The analysis shows that issues related to trust are central concerns for many participants. These include procedural concerns about transparency and distributional concerns about who will benefit from access to and use of "farmers' data". These concerns create scepticism about the value of `smart' technologies amongst some industry stakeholders, especially farmers. It also points to a divergence of expectations and norms between actors and institutions at the regime and niche levels in the emerging transition towards Smart Farming. Bridging this divide will require niche level interventions to enhance the agency of farmers and their local networks in these transactions, and, the cooperative design of new institutions at regime level to facilitate the fair and transparent allocation of risk and benefit in farming data information chains.
10 pages, Enormous quantities of data are generated through social and online media in the era of Web 2.0. Understanding consumer perceptions or demand efficiently and cost effectively remains a focus for economists, retailer/consumer sciences, and production industries. Most of the efforts to understand demand for food products rely on reports of past market performance along with survey data. Given the movement of content-generation online to lay users via social media, the potential to capture market-influencing shifts in sentiment exists in online data. This analysis presents a novel approach to studying consumer perceptions of production system attributes using eggs and laying hen housing, which have received significant attention in recent years. The housing systems cage-free and free-range had the greatest number of online hits in the searches conducted, compared with the other laying hen housing types. Less online discussion surrounded enriched cages, which were found by other methods/researchers to meet many key consumer preferences. These results, in conjunction with insights into net sentiment and words associated with different laying hen housing in online and social media, exemplify how social media listening may complement traditional methods to inform decision-makers regarding agribusiness marketing, food systems, management, and regulation. Employing web-derived data for decision-making within agrifood firms offers the opportunity for actionable insights tailored to individual businesses or products.
Online from publisher website. 5 pages., Describes a new Food Trust Consortium , run by IBM, using blockchain technologies to improve food traceability.
Force, J.E. (author / Department of Forest Resources College of Forestry, Wildlife and Range Sciences, University of Idaho, Moscow, ID) and Department of Forest Resources College of Forestry, Wildlife and Range Sciences, University of Idaho, Moscow, ID
Format:
Conference paper
Publication Date:
1984
Published:
UK
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 54 Document Number: C01051
Notes:
Phase 2, In: Moeller, G.H. and Seal, D.T., eds., Technology transfer in forestry : proceedings of a meeting of the International Union of Forestry Research Organizations, subject group s608; 1983 25 July - 1 August. London : Great Britain Forestry Commission, 1984. (Forestry Commission Bulletin No. 61) p. 74-80.
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 30 Document Number: D10562
Notes:
3 pages., via blog from Janzen Ag Law - online via AgriMarketing Weekly., Since big data arrived in agriculture a few years ago, I have watched companies struggle with how to address farmers' concerns with ag data privacy, security, and control. Some companies have started with a clean sheet of paper and drafted agreements that reflect what they actually do. Others have taken a short cut by cutting and pasting agreements from other industries. The result is that contracts for ag data collection, use and sharing are inconsistent and often miss the point-to communicate the company's intentions with users.
10 pages., via online journal., Findings indicate that analysis of news reports of agricultural injuries provide more current data than traditional surveillance databases.
35 pages, Despite the significance and growth of wind energy as a major source of renewable energy, research on the risks of wind turbines in the form of accidents and failures has attracted limited attention. Research that applies data analytics methodologically in this context is scarce. The research presented here, upon construction of a text corpus of 721 selected wind turbine accident and failure news reports, develops and applies a custom-developed data analytics framework that integrates tabular analysis, visualization, text mining, and machine learning. Topic modeling was applied for the first time to identify and classify recurring themes in wind turbine accident news, and association mining was applied to identify contextual terms associated with death and injury. The tabular and visual analyses relate accidents to location (offshore vs. onshore), wind turbine life cycle phases (transportation, construction, operation, and maintenance), and the incidence of death and injury. As one of the insights, more incidents were found to occur during operation and transportation. Through topic modeling, topics associated most with deaths and injuries were revealed. The results could benefit wind turbine manufacturers, service providers, energy companies, insurance companies, government bodies, non-profit organizations, researchers, and other stakeholders in the wind energy sector.
3 pages, Big data represent a new productive factor (the "new oil" for advocates) that generates new realities in agriculture. By adding an extra "cyber" dimension to current farming systems, big data lead to the emergence of new, complex cyber-physical-social systems. However, our understanding of the sustainability of such systems is still at a rudimental stage. In this critical review we attempt to shed some light on this topic, by identifying and presenting some issues that put in doubt the sustainability of big data agriculture. By using a punctuated equilibria lens, we argue that despite their contribution to the economic and environmental performance of farming, big data act as a speciation mechanism. Hence, they lead to new forms of intraspecific, interspecific and intergeneric competition, thus putting at risk the most vulnerable players of the game. We conclude by pointing out that to holistically address the interrelation between big data and agricultural sustainability we need a hybrid research line, which will combine the qualities of both technology-oriented research and critical social science.
Agricultural Communications Documentation Center, Funk Library, University of Illinois Document Number: C36965
Notes:
Agricultural Publishers Association Records, Series No. 8/3/80, Box 16, 6 pages., APA emphasizes need for gathering current agricultural statistics and reporting them promptly.
30 pages., via online journal., Effective communication requires a good message delivered through an effective channel and received by a receptive individual. When that communication is successful, the result is enhanced credibility and trust between the sender and the receiver. Telling the Extension story effectively requires both relevant, credible data to compose a clear message and appropriate communication channels to deliver the message to various audiences. This article describes the approach taken by Florida Extension to gather better statewide data to improve communication about the impact of its Extension work, primarily through the use of infographics. With credible data, and working together, Extension data analysts and communicators can enhance Extension’s reputation, trust, and support with key stakeholders.
United Nations Economic Commission for Europe, Geneva, Switzerland.
Format:
Guide
Publication Date:
2004
Published:
International
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 166 Document Number: C27781
Notes:
Posted in full text. Contains six chapters, each to be retrieved separately: 1. Principles, objectives and management issues in data dissemination. 2. Organizational aspects of dissemination. 3. Methods and tools. 4. Impact of the internet on information dissemination. 5. Learning in each other's classrooms. 6. Handling media crises.
New-Aaron, Moses (author), Semin, Jessica (author), Duysen, Ellen G. (author), Madsen, Murray (author), Musil, Kelsie (author), and Rautiainen, Risto H. (author)
Format:
Journal article abstract
Publication Date:
2019
Published:
USA: Taylor & Francis
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 25 Document Number: D10537
8 pages., via online journal., The Bureau of Labor Statistics (BLS) publishes annual statistics on occupational injuries and fatalities in the United States. The BLS fatality data include all agricultural workers while the non-fatal injury data only cover hired employees on large farms. In 2012, the Central States Center for Agricultural Safety and Health (CS-CASH) began collecting regional media monitoring data of agricultural injury incidents to augment national statistics. The aims of this report were: a) to compare CS-CASH injury and fatality data collected via print and online sources to data reported in previous studies, and b) to compare fatality data from media monitoring to BLS Census of Fatal Occupational Injuries (CFOI) data. CS-CASH media monitoring data were collected from a news clipping service and an internet detection and notification system. These data covered years 2012–2017 in seven Midwestern states (Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota). CS-CASH occupational fatality data were compared with aggregate CFOI data for the region during 2012–2015. Media monitoring captured 1048 injury cases; 586 (56%) were non-fatal and 462 (44%) were fatal. The numbers of occupational fatality cases from media monitoring and CFOI were nearly identical (280 vs. 282, respectively), and the distributions by type of injury were similar. Findings suggest that media monitoring can capture equal numbers of fatalities compared to CFOI. Non-fatal injuries, not captured by national surveillance systems, can be collected and tracked using print and electronic media. Risk factors, identified in media sources, such as gender, age, time, and source of the incident are consistent with previously reported data. Media monitoring can provide timely access to detailed information on individual cases, which is important for detecting unique and emerging hazards, designing interventions and for setting policy and guiding national strategies.
Agricultural Communications Documentation Center, Funk Library, University of Illinois Document Number: D08868
Notes:
Pages 215-256 in Ormrod, James S. (ed.), Changing our environment, changing ourselves: nature, labour, knowledge and alienation. United Kingdom: Palgrave Macmillan UK, London. 315 pages.
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 202 Document Number: D12151
Notes:
Online via AgriMarketing Weekly. 1 page., Data, analytics and technology company DTN acquires a global farm-level data source, Farm Market ID. Both share goals of helping agribusinesses support producers.
14 pages, via online journal, Designing effective policies for economic development often entails categorizing populations by their rural or urban status. Yet there exists no universal definition of what constitutes an “urban” area, and countries alternately apply criteria related to settlement size, population density, or economic advancement. In this study, we explore the implications of applying different urban definitions, focusing on Tanzania for illustrative purposes. Toward this end, we refer to nationally representative household survey data from Tanzania, collected in 2008 and 2014, and categorize households as urban or rural using seven distinct definitions. These are based on official administrative categorizations, population densities, daytime and nighttime satellite imagery, local economic characteristics, and subjective assessments of Google Earth images. These definitions are then applied in some common analyses of demographic and economic change. We find that these urban definitions produce different levels of urbanization. Thus, Tanzania's urban population share based on administrative designations was 28% in 2014, though this varies from 12% to 39% with alternative urban definitions. Some indicators of economic development, such as the level of rural poverty or the rate of rural electrification, also shift markedly when measured with different urban definitions. The periodic (official) recategorization of places as rural or urban, as occurs with the decennial census, results in a slower rate of rural poverty decline than would be measured with time-constant boundaries delimiting rural Tanzania. Because the outcomes of analysis are sensitive to the urban definitions used, policy makers should give attention to the definitions that underpin any statistics used in their decision making.
