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Agricultural Data Sharing in the New Zealand context Andrew Cooke www. rezare. com

About Us • Founded Rezare Systems in 2004 • Previously based at agricultural research institute • Product and service development for agricultural organisations • Mathematical models, genetics, livestock, pasture • New Zealand, Australia, United Kingdom

Using data in New Zealand agriculture • On farm strategic decision making • On farm tactical decision making and actions • Inputs (fertiliser, feed, seeds) – requirements, varieties, timing, placement • Outputs – provenance, timing, productivity, quality

Silo Effect • Few large and many small “custodians” of data • Relatively few government and “industry good” data sets • Organisations and producers still developing experience and understanding of digital information • Isolation of data both technical and organisational

Farm Data Initiatives Code of Practice • Transparency around rights and policies • Good security and privacy practices • Accreditation process Farm Data Standards • Common vocabulary to describe data • Targeted at developers and business analysts

Farm Data Initiatives Data. Linker Framework • Not a data hub or pipe • Not a database • Avoid building every connection from scratch • Reducing legal overheads while retaining control • Solving privacy and authorisation challenges • Support for onboarding organisations

Farm Data Initiatives Data. Linker Framework • REST and JSON framework • Based loosely on Open Ag Data Alliance • JSON-LD schemas defined by participants • Navigable data sets • OAUTH 2 and tokens – including producer permission • RFC 7591 dynamic registration, data access agreements • Discovery through datalinker. org service

Implementation example 1

Implementation example 2

Where to for spatial data? • Farm Data Standards uses INSPIRE catalogue definitions • Use cases • Farm boundaries, waterways, management areas • Fertiliser plans and applications • International alignment vs. local needs? Geo. JSON

Questions? Andrew Cooke www. rezare. com