Collaborative Research: HCC: Medium: Big Data on the Dairy Farm: Relational Transformations across Agricultural Occupations and Organizations with the Rise of Digital Technologies

合作研究：HCC：媒介：奶牛场大数据：随着数字技术的兴起，农业职业和组织之间的关系转型

• 批准号: 2211943
• 负责人: Pamela Hinds
• 金额: $ 30.52万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2211943&HistoricalAwards=false
• 关键词: Collaborative; Research; HCC; Medium; Big

This research will investigate how emerging technologies are transforming occupations and organizations, exploring the significant example of digital agriculture in dairy farming. The findings of this study will inform research on technology use and the changing nature of work. While research has shown that new digital technologies are best understood in social contexts, we know little about how changing relationships between people, sensors, data, animals, data science models and other important participants evolve. By studying those involved in digital agriculture dairy farming, supported by an understanding of how, when, and why they interact, this research will contribute to the discussion on how to apply data-driven technologies productively. The findings will also develop new theory about the relationship between big data and resource management by documenting their impacts on occupations and organizations. This research highlights how data science models contribute to such evolving relations and how relational transformations, in turn, shape the models. This project's theoretical framework is built upon key contributions of the scholarship exploring technology, data, and organizing before proposing a relational framework for studying digital agriculture. The work employs a comparative mixed-method study with three main project goals: (1) to explore evolving relations in digital agriculture and the occupational and organizational consequences of them, (2) to generalize the findings and derive theoretical insights for other contexts where the rise of data-driven technologies may prompt similar relational transformations, and (3) to assess how insights about evolving relations might aid in design and deployment of the data science models and with them sensors, data streams, and the like. Mentoring of graduate and undergraduate students will serve as an example of how to integrate data science and social science inquiries in research projects while providing students with essential fieldwork, analytical, and publishing skills.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项研究将调查新兴技术如何改变职业和组织，探讨奶牛农业数字农业的重要例子。这项研究的发现将为技术使用和工作性质不断变化的研究提供信息。虽然研究表明，在社会环境中最好理解新的数字技术，但我们对人们，传感器，数据，动物，数据科学模型和其他重要参与者之间的关系如何变化而了解。通过研究参与数字农业乳业农业的人，并在对它们如何，何时和为什么相互作用的理解的支持下，这项研究将有助于讨论如何有效地应用数据驱动的技术。这些发现还将通过记录其对职业和组织的影响来发展有关大数据和资源管理之间关系的新理论。这项研究强调了数据科学模型如何有助于这种不断发展的关系以及关系转换如何构成模型。该项目的理论框架是基于奖学金探索技术，数据和组织的关键贡献，然后提出了研究数字农业的关系框架。 The work employs a comparative mixed-method study with three main project goals: (1) to explore evolving relations in digital agriculture and the occupational and organizational consequences of them, (2) to generalize the findings and derive theoretical insights for other contexts where the rise of data-driven technologies may prompt similar relational transformations, and (3) to assess how insights about evolving relations might aid in design and deployment of the data science models and with them传感器，数据流等。对研究生和本科生的指导将作为如何在研究项目中整合数据科学和社会科学询问的一个例子，同时为学生提供基本的现场工作，分析和出版技能。这项奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和广泛影响的评估来通过评估来支持的，这是值得的。