Suchergebnisse

ObjectivesTo create an anonymised research-ready data resource of farm households in the UK to generate evidence to support policy development, implementation and evaluation; improve understanding of farm family socio-economic characteristics; and assist stakeholders interested in understanding the health and well-being, resilience and prosperity and spatial properties of farming communities.
MethodsThe ADARC research-ready data resource is being created in each nation of the UK. Each core dataset links agricultural datasets with individual- and household-level population data from the Census 2011. The farm business data is drawn from a number of sources (the Inter Departmental Business Register, EU Farm Structure Survey 2010 and Rural Payments data), which presented many data preparation challenges when linking to the Census of Population. Each core dataset will be linked to the health and education data available for that nation. Where possible, the ADARC datasets have been harmonised to allow federated querying across the UK.
ResultsThe ADARC core datasets are complete in Wales and near completion in England and Scotland. Work is also well advanced in Northern Ireland. To the best of our knowledge, these are the first datasets linking agricultural data to individual- and household-level data at a population level. We will report the challenges experienced in linking farm business data with data at the household and individual level. This will include a description of the data preparation steps, the challenges encountered and solutions utilised at each stage of building this complex dataset from numerous, very different 'parent' datasets.
The structure and content of the core datasets will be presented as well as the potential benefits to researchers investigating the individual, household and community dimensions of agricultural research.
ConclusionAgriculture is currently facing a range of challenges with little known about the impact on farmers and farming households. ADARC introduces a new, powerful and versatile resource that will help inform debate and potentially lead to better outcomes on a range of issues relevant to farmers and farming communities.

ObjectivesADARC is a partnership of six government departments and three research institutions across ADR-UK aiming to build four Research Ready Datasets about farming households. A|ARC requires government data linking experts to work closely with agricultural statisticians and academics across traditional boundaries pooling a wide range of data and expertise.
MethodsThe ADARC partnership aims to build a model of collaborative working for administrative data research. ADARC brings together those collecting data with those linking and analysing de-identified data and eventually those using results to develop future policies. The data is from several different sources at individual, household and business levels requiring new methodologies developed by this collaboration. ADARC is also working between all four ADR centres to share learning across the ADR network building relationships for future projects beyond agriculture. The linkage process has been different in all four nations but this has offered new learning for all involved.
ResultsDue to the Covid-19 pandemic, Phase 1 of the project has been slower than hoped. However, ADARC has shown that it is possible to conduct a truly UK-wide four nation project. Data linking is underway in all four nations bringing together data on individuals, households and businesses and analysis has begun in Wales and England. The project to date has faced the usual challenges of data acquisition and data quality issues which the partnership approach has been vital for overcoming. Despite this, we've demonstrated that there's a huge level of enthusiasm for working together across organisational barriers. ADARC has just been funded for Phase 2 to expand the datasets in scope and explore the feasibility of linking in spatial data.
ConclusionADARC has created a model which demonstrates that partnership working is essential for fully achieving the objective of ADR UK of unlocking the potential of administrative data. The lessons of ADARC also provides a powerful case study for future cross-UK projects far beyond agriculture.

ObjectivesThe AD|ARC Administrative Data: Agriculture Research Collection is an ambitious and original linkage project, bringing together information about farmers and farming households from several sources. When complete, this research-ready dataset will assist in addressing three broad themes: health and well-being, prosperity and resilience, and engagement with agri-environment.
ApproachThe dataset is being constructed from information drawn from survey, census, and administrative sources. Necessarily, this includes working across government departments to ensure comprehensive coverage of farm, business, education, and health data. Similarly, data owners, processors, and researchers are working closely to ensure the resultant dataset meets expectations. Alongside this cross-sectoral aspect, the work is also cross-jurisdictional, with the intention being for the data to capture information about farms, farmers and farming households from across the UK.
ResultsRather than focus on the detail of the substantive research that AD|ARC will enable, this paper discusses some of the challenges and successes of this linkage project to date. Drawing on the experience of the teams from across the UK (England, Northern Ireland, Scotland, and Wales), the first part will discuss challenges faced in linkage of this multi-faceted project, alongside how the population census is being utilised to better understand farming communities, through the identification of both farming households and workers. Secondly, a broader discussion of the challenges and sensitivities of working across government departments and administrations will be presented, alongside ways of working developed to recognise and overcome these.
ConclusionThe AD|ARC project will result in an invaluable resource to better understand the farming community, which in turn will help to better inform policy debate and decision making. Alongside this, the process of creating the dataset has offered opportunities for learning and insight across a range of issues.