AD-ARC (Administrative Data - Agricultural Research Collection): Linking Farms to Individual, Household and Business Data to create a Research-Ready Dataset for ADR UK.

IF 2.2 Q3 HEALTH CARE SCIENCES & SERVICES
International Journal of Population Data Science Pub Date : 2026-07-06 eCollection Date: 2026-01-01 DOI:10.23889/ijpds.v11i5.3682
Nathan O'Connor, Beth Allen, Esther Lewis, Sarah Cummins, Sian Morrison-Rees
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Abstract

The aim of this project was to produce a complete record of farms in England to be linked to individual, household and business data, enabling the creation of a de-identified research-ready dataset (RRD) of farming individuals, households and businesses in England. Following lessons learned from the first phase of this project, a 'farm spine' was created using two farms data sources, 2021 June Survey of Agriculture and Horticulture and 2020-2022 Rural Payments Agency subsidy payment information. This spine utilised address and contact information at individual, farm holding, and business level, enhancing the matching potential when linking to census and business data. Deterministic linkage methods were used to match farms with associated households and businesses. The varied and nuanced nature of the data sources meant a non-standard approach was required when structuring the data for linkage, as well as ongoing feedback and collaboration between stakeholders to best deliver an optimised, high-quality bespoke dataset. The resulting dataset links geographic and farm activity data, subsidy payments, business ownership and turnover information, and characteristics of farming households. This presentation includes details of the data preparation, challenges encountered, and solutions utilised at each stage of building this complex dataset. To our knowledge, the AD|ARC RRDs are the first datasets linking agricultural data to individual and household-level data at a population level. They provide an invaluable resource that will inform policymakers seeking to support agricultural and rural communities. Its multi-organisational approach and use of varied data sources highlight lessons learned for future data linkage projects.

AD-ARC(行政数据-农业研究收集):将农场与个人、家庭和商业数据联系起来,为ADR UK创建一个研究就绪的数据集。
该项目的目的是制作一个完整的英格兰农场记录,将其与个人、家庭和商业数据联系起来,从而创建一个英格兰农业个人、家庭和企业的去识别研究就绪数据集(RRD)。根据从该项目第一阶段吸取的经验教训,利用两个农场数据源,即2021年6月农业和园艺调查和2020-2022年农村支付机构补贴支付信息,创建了“农场脊柱”。该脊柱利用了个人、农场和商业层面的地址和联系信息,增强了与人口普查和商业数据相关联的匹配潜力。采用确定性关联方法将农场与相关家庭和企业进行匹配。数据源的多样性和细微差别意味着在构建链接数据时需要采用非标准方法,以及利益相关者之间的持续反馈和协作,以最好地提供优化的、高质量的定制数据集。由此产生的数据集将地理和农业活动数据、补贴支付、企业所有权和营业额信息以及农户特征联系起来。本演讲包括数据准备的细节,遇到的挑战,以及在构建这个复杂数据集的每个阶段使用的解决方案。据我们所知,AD b| ARC rrd是第一个将农业数据与人口层面的个人和家庭数据联系起来的数据集。它们提供了宝贵的资源,将为寻求支持农业和农村社区的决策者提供信息。它的多组织方法和各种数据源的使用突出了未来数据链接项目的经验教训。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
386
审稿时长
20 weeks
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