Big data represent a pioneering development in the field of agriculture. By producing intuition, intelligence, and insights, these data have the potential to recast conventional process-driven agriculture, plotting the course for a smarter, data-driven farming. However, many open issues about the use of big data in agriculture remain unanswered. In this work, conceptualizing smart agricultural systems as cyber-physical-social systems, and building upon activity theory, we aim at highlighting some key questions that need to be addressed. To our view, big data constitute a tool reciprocally produced by all the actors involved in the agrifood supply chains. The constant flux of this tool and the intricate nature of the interactions among the actors who share it complicate the translation of big data into value. Moreover, farmers’ limited capacity to deal with data complexity, along with their dual role as producers and users of big data, impedes the institutionalization of this tool at the farm level. Although the approach used left us with more questions than answers, we suggest that unraveling the institutional arrangements that govern value co-creation, capturing the motivations of farmers and other actors, and detailing the direct and indirect effects that big data (and the technologies used to generate them) have in farms are important preconditions for setting forth rules that facilitate the extraction and equal exchange of value from big data.

大数据代表着农业领域的开拓性发展。通过产生直觉，智慧和见解，这些数据有可能重铸传统的过程驱动型农业，从而为智能化，数据驱动型农业指明了方向。但是，关于农业中使用大数据的许多未解决问题仍未得到解答。在这项工作中，将智能农业系统概念化为网络物理社会系统，并基于活动理论，我们旨在突出一些需要解决的关键问题。我们认为，大数据构成了农业食品供应链中所有参与者相互产生的工具。该工具的不断变化以及共享该工具的行为者之间互动的复杂性，使得将大数据转化为价值的过程变得复杂。此外，农民处理数据复杂性的能力有限，加上他们作为大数据的生产者和用户的双重角色，阻碍了该工具在农场一级的制度化。尽管所使用的方法给我们带来的问题多于答案，但我们还是建议您阐明控制价值共同创造的制度安排，抓住农民和其他行为者的动机，并详细说明大数据（以及所使用的技术）的直接和间接影响。在农场中拥有）是制定规则的重要前提，这些规则有助于从大数据中提取和平等交换价值。