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November 12, 2015
2015 Crop Insurance Workshop Presentations
For additional information about this topic or any other questions regarding Kansas Farm Management, please see the following websites, or contact us at the phone numbers below.
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September 26, 2017
Precision Ag and Technology Articles
1
Who Can Own Farm Data?
Terry Griffin (twgriffin@ksu.edu)
Kansas State University Department of Agricultural Economics ‐ September 2017
In the previous article, the notion that farm data aggregated into a community truly fit the concept of
‘big data’ was demonstrated. For many agriculturists, the more important issue is data ownership. The
question of who owns farm data goes back at least to the advent of precision agriculture in the 1990s.
Data ownership, privacy, and security have cyclically been hot topics since then but have recently
peaked with ‘big data’. When discussing ownership of physical goods such as commodities, machinery,
and farmland, it is intuitive what ‘ownership’ means. Farm data does not fit many preconceived
notions of ‘ownership’ like these physical examples.
The legal perspective of farm data ownership has been addressed individually by Extension agricultural
attorneys including Tiffany Dowell and Shannon Ferrell and at least one attorney in private practice, Todd
Janzen. Complementing their work, I describe how economic principles apply to farm data that are
digital and have very different characteristics than physical goods. Copies of digital data can be made
at relatively zero cost and are indistinguishable from the original. Given that copies are identical to
each other and the original, very minimal control exists over what happens to that data once copies
have been made available to another party. Multiple entities (e.g. farmers, landowners, input
suppliers, soil sampling services, aggregators, lenders, etc.) may have partial access to viable copies of
the same farm data.
Applying the economic principles of public goods versus private goods and excludability versus non‐
excludability helps to make this point. Ownership of private goods implies that the owner may exclude
others from enjoying their property. Public goods are not privately owned and no one can exclude
others from enjoying these goods. To fully understand this, the concept of “non‐rival” goods need to
be considered and applied to farm data. Private goods are typically not ‘non‐rival’. Farm data are
considered “non‐rival” because the consumption or usage of data by one person does not alter
another person’s ability to consume or use that same data (see our recent paper for more details).
Classic examples of non‐rival goods are books and movies; multiple people can read the same book
without any loss of value to any other readers. Economic theory suggests that there is no loss of utility
by the next person enjoying the same book. A recent paper described examples of agricultural non‐
rival goods as weather reports, commodity market information, and farm data. The value that the
initial user receives from accessing data or information is not affected by another user accessing the
same information. Multiple entities can consume farm data without diminishing the initial value
enjoyed by the first or subsequent users of that data.
Kansas State University Department Of Agricultural Economics Extension Publication …
December 19, 2019
Financial Management
https://www.ers.usda.gov/topics/farm-economy/farm-sector-income-finances/assets-debt-and-wealth …
April 13, 2020
Ag Law Issues
legislation – it’s the topic of today’s post.
Change …
August 24, 2020
Ag Law Issues
activities – it’s the topic of today’s post.
Definition …
November 13, 2020
Ag Law Issues
rental income – it’s the topic of today’s article.
Reporting …
January 15, 2021
Ag Law Issues
Law course – that’s the topic of today’s post.
Course …
February 11, 2021
Economics
KEY CHALLENGES & HOT TOPICS
Agricultural Economics
Packing …
May 21, 2020
Industry Economics & Trade
decision-making. Recently the topic of exports and
imports …
August 4, 2020
Monthly Meat Demand Monitor (Prior Years)
foods, and E.coli are the topics heard or
read most about …