Livestock data – Is it there and is it FAIR? A systematic review of livestock farming datasets in Australia

Bahlo, Christiane; Dahlhaus, Peter

doi:10.1016/j.compag.2021.106365

Cited by 9 publications

(1 citation statement)

References 16 publications

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“…Fully automated assessment tools are unable to capture any FAIR metrics in scenarios where a dataset doesn't at least have a Uniform Resource Locator (URL) and a machinereadable metadata record. Systematic analyses testing the FAIRness of agricultural datasets using the FAIR Evaluation Services (Bahlo and Dahlhaus 2021) and the F-UJI API (Petrosyan et al 2023) illustrate both the potential and the limitations of automated assessment tools.…”

Section: Limitations Of Existing Fair Assessment Toolsmentioning

confidence: 99%

Advancing FAIR Agricultural Data: The AgReFed FAIR Assessment Tool

Bahlo

2024

Data Science Journal

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The FAIR principles provide guidance for improving the findability, accessibility, interoperability and reuse of research data and other digital objects. The Agricultural Research Federation (AgReFed) has developed a FAIR implementation consisting of policies, resources and tools to enable FAIR agricultural data in Australia. It prescribes minimum acceptable data standards and an associated set of FAIR metrics for agricultural research data. Existing FAIR assessment tools were examined and found to have limitations in serving the purposes of AgReFed.The AgReFed FAIR assessment tool addresses these needs with novel features to help improve FAIRness of datasets and other digital resources. By providing the ability to assess and subsequently re-assess datasets while also enabling users to add comments, it facilitates building work lists that support and document the improvement in FAIRness. Other innovative features include customisable FAIR metrics, storage of assessment results, a versioning system and inbuilt help resources. In addition to userfriendly reporting of AgReFed standards compliance, the integrated automated F-UJI FAIR assessment API provides a supplementary set of machine-readable FAIR scores.The AgReFed FAIR Assessment Tool has been deployed for public use and released as open source to help data custodians enact FAIR principles in domains and data communities within and beyond Australian agriculture.

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Section: Limitations Of Existing Fair Assessment Toolsmentioning

confidence: 99%

Advancing FAIR Agricultural Data: The AgReFed FAIR Assessment Tool

Bahlo

2024

Data Science Journal

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Digital technology and on-farm responses to climate shocks: exploring the relations between producer agency and the security of food production

Richards,

Messner,

Higgins

2024

Agric Hum Values

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Recent research into climate shocks and what this means for the on-farm production of food revealed mixed and unanticipated results. Whilst the research was triggered by a series of catastrophic, climate related disruptions, Australian beef producers interviewed for the study downplayed the immediate and direct impacts of climate shocks. When considering the changing nature of production under shifting climatic conditions, producers offered a commentary on the digital technology and data which interconnected with climate solutions deriving from both on and off the farm. Perceptions of digital technologies were mixed. Some viewpoints outlined how data driven climate solutions supported on farm planning and decision making, helping to manage climate risks and shocks. However, alongside these narratives, concerns were raised about satellite-based sustainability surveillance and their implications for producer agency. These concerns include the data-informed actions of non-farming third parties, such as bank loan call-ins for properties perceived to be a climate risk, remote surveillance of ground cover, and the commercial re-appraisal of pastoral lands as carbon sinks. Digital solutions to climate shocks thus emerge as inherently ambivalent, a response to shocks and a potential catalyst for renewed crisis. Drawing upon the theoretical lens of relationality, we argue that digital data are increasingly entangled with other material and non-material elements that may disrupt and/or reconfigure the management of farming and with that, the future security of food production. In some instances, data-based solutions to climate risks and shocks present even greater risks to producer agency than climate risks and shocks themselves.

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