Farm Data Usage - Coming to Terms

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:

• Until someone can clearly explain the benefits, nobody will share their data

• How will anyone know what happens after they share their data

• We need to clearly define who owns farm data

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.