Abstract
Commercial farmers are under increasing pressure to collect data for decision-making, regulatory compliance, and reporting down the supply chains. These data demands are intensifying, as societal pressures grow for greater sustainability, food safety, and accountability. While manual data collection is common, the process is increasingly automated using sensors. Services frequently employ specific interfaces, and collected data is recorded into many, often proprietary databases, limiting interoperability. The result is overwhelming complexity for farmers, duplication of effort, missed opportunities to access and compare different datasets, and potential regulatory and competitive failings. Tensions exist between the business models of agricultural service providers and the farmers they support. These need to be surfaced and addressed if the sector is to fully benefit from digitalization. Web3.0 technologies and protocols – in particular distributed systems – may offer some opportunities as they provide data interoperability, tools to address data ownership issues, edge computing, and decentralized data. With illustrative case examples from New Zealand farms, this chapter identifies some of the key barriers that need to be addressed and critically discusses how digital innovation and adoption may be accelerated in farming systems.