By Richard Heath
AgTech Takeaways - the expanded menu (part 4): In March, I participated in an Austrade-facilitated Australian Agtech Delegation to the US and wrote a blog about my takeaways with four main points of conclusion. Over the next month each of those key points - integrated systems approaches, farming practice adaptation, genomics / computational breeding and open data - will be expanded on in turn.
4. Technology developers are all talking about the need for open data platforms and collaboration. Hopefully this is more than lip service and results in genuine change which leads to true data portability and functioning data markets. This will be one of the most critical things to get right to speed adoption and confidence to participate in digital agriculture.
As someone who has attended precision agriculture conferences for the past 20 years, one of the most refreshing aspects of the World Agri-Tech Summit was the culture shift to open data. Virtually every single speaker acknowledged the need for their platform to communicate with and be relevant to every other digital platform.
In the early stages of the development of precision agriculture, products were developed very much on a standalone basis with unique file types and proprietary systems making it difficult if not impossible for data to be transferred between platforms. In some ways this was understandable as early technology was developed to achieve specific individual tasks. The understanding that the data collected was potentially more useful when aggregated and combined with other data for a systems-based analysis was still far off. Early precision ag adopters will know the pain of exporting strange file types on weird card formats and using a variety of software packages to do even the most basic analysis.
"A FAIR approach to data collection provides confidence that the investment in obtaining data will always be positive …"
As the realisation grew that aggregated multi-input data was where the real value was going to be delivered in digital agriculture, the lack of interoperability with legacy systems started to become evident. Thankfully almost all technology developers are now advocating for interoperability and realising that the way to attract people onto their platforms is to make them open and accessible rather than closed and proprietary. Recent examples such as CNH making their data available on Monsanto’s Field View platform as well as through Microsoft’s Azure Cloud are typical of the change in approach from major ag technology companies wanting to appear as open as possible.
The importance of true interoperability should not be underestimated as a key factor in faster adoption of digital agriculture. Industry interviews conducted through the course of the P2D project (Accelerating Precisions Agriculture to Decision Agriculture) identified lack of interoperability as a major impediment to uptake across all agricultural sectors.
Agriculture still has a way to go before a functional and open data market exists that enables the sorts of products that are emerging in other markets. For an idea of what those products look like in a more mature data market, have a look at Zapier, a tool that can move information between more than 1000 web-based apps. The Farming Team is an early example of a similar service for agriculture that aims to transfer data between multiple farming, farm management and finance platforms.
The FAIR data principles (findable, accessible, interoperable and reusable) describe the way data can be collected so that it’s value can be maximised no matter what the original intended use was. A FAIR approach to data collection provides confidence that the investment in obtaining data will always be positive, because if the original purpose for collection does not provide a return then the data can still be used for another purpose that does add value.
All the technology developers that presented at the World Agri-Tech Summit in some way acknowledged open or FAIR data and committed to their products conforming to those principles. If this language is reflected in what they actually produce, a big obstacle blocking digital ag technology adoption will be removed.