Determining a realistic national definition of agricultural property and an associated draft data model to enable future creation of a national agricultural property dataset.
Australia’s agricultural sector currently lacks a consistent map (spatial database) containing accurate boundaries of agricultural properties. In fact, no unified definition of an agriculture property for all types of agriculture (i.e. grain, horticulture, livestock, hobby farms etc.) exists which can act as bounds within which to create this dataset. Agricultural property boundaries are a fundamental dataset that present a massive potential value uplift for informed and timely decision making on properties. However, to define and create such a dataset, consultation would be required with all the stakeholders who would be involved in creating and managing such a product, including producers, state and federal government departments, technology organisations, and service providers.
This research project would not have been possible without the generous support and contributions from many organisations and individuals. Most notably, the project was conducted in collaboration with project sponsors Meat and Livestock Australia and Geoscape. The project outcomes draw on the many contributions from stakeholders who were interviewed, attended workshops, or responded to surveys.
The results of desktop research, along with a collaborative stakeholder engagement process utilising an online survey, phone interviews and workshops were collated and integrated to develop a nationally consistent definition of agricultural property and an associated draft data model. Stakeholder consultation involved 23 phone interviews, three workshops held in Perth, Canberra and Brisbane, and 58 responses to an online use case survey.
Biosecurity – measures designed to protect the population against harmful biological or biochemical substances – was selected as the key use case and acted as the key driver for the national agricultural property definition and data model. This use case has the most wide-ranging set of requirements of any application and therefore necessitates an inclusive definition of agricultural property. However, a broad driver introduces the risk that requirements become too complex and inhibit the development of the dataset. Hence, sub-classes were adopted for the definition and associated with stages of dataset development along with levels of completion and accuracy.
The draft data model includes description of the product and its purpose, the spatial representation of the dataset, a data model schema diagram, attributes, and a data dictionary, potential contributors, metadata, access levels, potential business models, data history, and ideas for production, maintenance and delivery. It describes a minimum viable product, focusing on initial production of high accuracy, complete data for sub-class one of the definition.
Agricultural property data is a foundation dataset enabling many applications. A nationally consistent definition of agricultural property and an associated data model will improve efficiency, minimise risk, and increase profitability for countless agricultural use cases by enabling an accessible, authoritative source of current, consistent and complete agricultural property data. Ultimately, the industry benefits are economic, but this is comprised of many process and system improvements. Next steps for this process include public release of the project reports which will be used with stakeholders to determine the value of a future project to implement the draft data model and begin creating the dataset.
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