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Developing and implementing interoperative agricultural data exchange standards
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Open data and interoperability standards: Opportunities for animal welfare in extensive livestock systems

PhD (Confirmed 2021): Chris Bahlo

Supervisors: Assoc Prof Peter Dahlhaus and Assoc Prof Helen Thompson

Research overview

Extensive livestock farming constitutes a sizeable portion of agriculture and contributes to feeding a growing human population. The livestock industry is adopting technologies under the banner of Precision Livestock Farming (PLF) to help meet higher production and efficiency targets as well as help to manage the multiple challenges impacting the industry, such as climate change, environmental concerns, globalisation of markets, increasing rules of governance and societal scrutiny especially in relation to animal welfare. PLF is particularly dependent on the acquisition and management of data and metadata and on the interoperability standards that allow data discovery and federation. A review of interoperability standards and PLF adoption in extensive livestock farming systems identified a lack of domain specific standards and raised questions related to the amount and quality of public data which has potential to inform livestock farming. A systematic review of public datasets, which included an assessment based on the FAIR principles (data must be findable, accessible, interoperable and reusable) was developed. Custom software scripts were used to conduct a dataset search to determine the quantity and quality of domain specific datasets yielded 419 unique datasets directly related to extensive livestock farming. A FAIR assessment of these datasets using a set of general metrics showed a moderate level of compliance and suggest that domain specific FAIR metrics may need to be developed. A case study was designed to explore the potential of public datasets in informing decision support in relation to livestock welfare, using the scripts previously developed. Welfare elements were extracted from Australian welfare standards to guide a dataset search. It was found that with few exceptions, these elements could be supported with public data. The development of a geospatial animal welfare portal including these datasets explored and confirmed the potential for using public data to enhance livestock welfare.

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