Data sharing platforms: How value is created from agricultural data

计算机科学 数据共享 商业价值 价值(数学) 大数据 数据科学 过程(计算) 数据管理 打开数据 维恩图 知识管理 万维网 数据库 数据挖掘 经济 微观经济学 病理 数学教育 机器学习 利润(经济学) 替代医学 操作系统 医学 数学
作者
Matthew Wysel,Derek Baker,William Billingsley
出处
期刊:Agricultural Systems [Elsevier BV]
卷期号:193: 103241-103241 被引量:74
标识
DOI:10.1016/j.agsy.2021.103241
摘要

Across agriculture, data is produced, enriched, and consumed through the centuries-old practices of producing food and fibre. The adoption of Smart Farming and its connected services and techniques accelerates agriculture's dependence on data, yet the process of creating value from data is not well understood. What assets and management decisions comprise the process of creating value from data? What are the properties of this process, and where should resources be invested to increase the value created from agricultural data? We extend platform economics theory with the results from a recent systematic literature review of Big Data in Smart Farming to show the creation of value from data occurs in Data Sharing Platforms. Data sharing platforms are systems that connect the layers of the 'platform stack' with pertinent management tasks to create value from data. We illustrate this arrangement as a sectioned, three-circle Venn Diagram and evaluate the efficacy of common data management techniques in the creation of value from data. This paper concludes that value is created from data only when each of the components of data sharing platforms are present and that the operation of a data sharing platform describes the process that takes data as an input and produces value as an output. Further conclusions relate to commercial and institutional aspects of the creation of value from Smart Farming data. The proposed model is useful for evaluating production processes that create value from data. This paper details several avenues for extension. Productive models of systems that rely on data as a core asset may now be assembled. Policies that trade off technical characteristics of data with social impacts of data may now be approached. Questions surrounding data ownership may be considered with greater clarity.
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