Coming to terms with farm data?usage
J. Matthew Pryor
Supporting innovators at the intersection of agri-food system transition and climate solutions
In?How to Read a Book,?Adler & Van Doren argue that in order to properly understand an author's intent, you must?come to terms?with that author.
Unless the reader comes to terms with the author, the communication of knowledge from one to the other does not take place
I think we have a similar problem with the conversation around farm data. We tend to treat farm data like it is just one thing, and that there is only one thing to worry about -?to share?or?not to share.
The conversations tend to be along these lines:
It is not the one thing
Farm data is many things and there are important differences in how data is used to create value on-farm.
If we don't create a clearer definition for these different modes of use, we can't have a well-informed conversation about the?benefits and harms?that are associated with the deeper adoption of?digitally native?solutions.
Let's start with some different ways that data can be used:
Integration
This is probably the most common usage mode and can create value by combining strengths.
Different existing applications and platforms can read and write data between each system and in doing so create solutions that are better and more useful than the individual systems.
Interchange
Data in one place can often be needed in another place.
It is common that data from existing systems can make it more efficient to comply with reporting requirements. The ability to take data from one system and export it to another can ease administrative and compliance obligations.
Aggregation
There are often many places where data gets collected and stored which can create challenges of its own.
This is an approach to bringing data together from many different places into one single solution. An underappreciated benefit of this approach is the ability to combine many data streams together that can create new and deeper insights or solve specific and proprietary needs.
Migration
Farm management platforms aren't one-size-fits-all and sometimes you can outgrow one.
When you want to take all your data and move to a new system, you need the ability to migrate all your data, and for that to be a smooth process that brings along everything you need.
Taking it up a notch
If we're going to make progress in this conversation, we can't simplify things so much that we lose important distinctions.
By discussing the different ways that farm data can be used and the different ways it can add value or create risk, we can improve everyone's understanding of how to ask better questions and develop better answers.
Bachelor in IT Management
2 年It's just like life, if you let fear to stop you from moving forward, then you are losing opportunities. And since the future of farms is AgriTech, the first ones to adopt this methodologies will have many advantages over their competitors. But from the farmers perspective, I understand their fears, and the DPI's farmdecisiontech site is exposing some farms data as an example of AgriTech implementations, which I don't know if that helps the farming sector to understand the real exposure of their data and if systems can be trusted or not. Btw, I'm also commenting here to get some exposure into the Australian AgriTech sector, you may want to hire me :)
Co-Founder at Pairtree Intelligence Pty Ltd
2 年J. Matthew Pryor Interesting article and a great step to further discussing and defining the benefits of Farm data. The first and foremost point that any Australian farmer and Agtech company should be thinking about to define these themes and benefits is to recognise the work that has already been done in this space and not recreating the wheel. The National Farmers Federation has developed the V1 Voluntary Farm data code https://nff.org.au/programs/australian-farm-data-code/ (declaring I'm a framer and Agtech rep for this committee). The NFF committee is now seeking input on the V2 version of the code. Pairtree has been working in this space for over 4 years, Integrating with well over 100 Agtech companies. Always 'Complementing and NOT competing' with the solution provider, leveraging their services to benefit new solutions and insights for Farmers. Pairtree sells 'Integrations (Connections) NOT Information' this business model ensures that farmers Opt-in to Integrations that add value and ensures that the Agtech company fits the Business and Budget for the farm data that is required to be collected and managed. We have learnt that 'Centralisation' has less value than 'Convergence' which loosely fits in your 'Interchange'.
Founder & Managing Director at Source Certain International | Leader in Supply Chain Integrity and Transparency | Expertise in Forensic Provenance | Speaker
2 年Good discussion J. Matthew Pryor and commentary Andrew Coppin and Philip Browning. My intersection with this area has been that around transparency with if supply chain where data-> information -> sharing is obviously critical but have called out at Ag Tech conferences for a number of years the amorphous use of the word data. Ag does not operate in a vaccuum and the colour behind this discussion is one where we are all a bit on edge about our data - who has it and who’s selling it etc. we must be specific and talk about the sort of data and it use. I’m new to joining the NFF farm data working group with my experience being beyond the farm gate as a value creating opportunity but it is clear to me that there is great concern over the use of their data with lots of discussions which end up with a call for more transparency about how it it is and will be used. This is a symptom I propose of a lack of trust which I don’t think is just an Ag/AgTech driven issue (as noted above) but for us to navigate it there is a need for clear and defined communication from a starting point which clearly acknowledges the farmers ownership of their data.
Researcher, Entrepreneur, Trusted Adviser, Non-Executive Director
2 年During the recent forum on the agricultural data marketplace I noted great variety in how the language of data sharing was being used and how it was not clearly defined - is data sharing actually "sharing" or rather more generally the transfer, exchange and generalised provision of data? I would argue that "sharing" is a specific and constrained set of circumstances, rather than the generalised provision of data that is the dominant meaning applied to the language of data sharing in enterprise data governance regimes. If we are more careful about this language there is potential for improved trust through the social and data ethics it engenders. However, to do so one confronts issues of power, and who defines what data sharing is and whether its use has been co-opted by certain actors. "is data sharing really sharing" ? John G. Keogh Laurens Klerkx Dr David Christian Rose Robert Finger Simon Fielke
Founder & CEO
2 年Matt. Certainly agree with your overarching theme at a time I am trying to understand what everyone who is trying to harness the power of "Farm Data" in all its forms is trying to achieve - that's not easy! One of the many challenges that needs honest discussion from an Agritech perspective is how companies who have or intend to have the assessment of combinations of data ( i.e. . some derived from their own customers combined with other sources to make informed insights ) as part of their monetization strategy fit into some of the models being touted. I see that its challenging for some agritechs, no matter how collaborative, to be told by large firms or aggregators to centralise data so other people with more skills, computing power and /or resources can "manage, merge and monetize it(data)" for their own gain...not as a service offered to the Agritechs for the benefit of their customers. Whilst the vast majority of agritechs I know concur that the data derived from their efforts is ultimately the customers, and provide them access to it, the irony would be if the sharing of that intimate data could, if abused, ultimately be to the detriment of their own business models.