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Big data implications - Terry Griffin - 6

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Big Data Implications for Agriculture Terry Griffin, PhD, CCA Cropping Systems Economist Department of Agricultural Economics @SpacePlowboy #PrecisionAg #BigData #FarmData #EOCC17 Eastern Ontario Crop Conference Kemptville, ON February 14, 2017
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Page 1: Big data implications - Terry Griffin - 6

Big Data Implications for Agriculture

Terry Griffin, PhD, CCA

Cropping Systems Economist

Department of Agricultural Economics

@SpacePlowboy

#PrecisionAg #BigData #FarmData

#EOCC17

Eastern Ontario Crop Conference

Kemptville, ON February 14, 2017

Page 2: Big data implications - Terry Griffin - 6
Page 3: Big data implications - Terry Griffin - 6

Farmer’s Use of Precision Ag

0

25

50

75

100

1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Per

cent of

Far

ms

Automated Guidance Lightbar Automated Section Control Precision Soil Sampling

Yield Monitor Yield Monitor with GPS Variable Rate Fert. Variable Rate Seed

Page 4: Big data implications - Terry Griffin - 6

www.presentationmagazine.com

Page 5: Big data implications - Terry Griffin - 6

www.presentationmagazine.com

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www.presentationmagazine.com

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Data Analysis Service Offerings

82.0%

38.7%

19.5%

12.3%

9.2%

0% 50% 100%

Print Maps for Customers(Yield/EC/Soil Maps, etc.)

No Aggregate Data; Individual FarmData Only

Data Aggregated Among Farmers ButNot Outside the Dealership

Data Aggregated Among FarmersIncluding Those Outside the

Dealership

Do Not Help Customers With TheirFarm-Level Data

% of Respondents

2015 Base: 261 respondents

Erickson & Widmar, 2015

Managing Farm-Level Data to Assist Customers in Decision Making

Small data

Big data

Big data

Page 9: Big data implications - Terry Griffin - 6

Precision profitability over time

0%

10%

20%

30%

40%

50%

60%

70%

80%

2003 2004 2005 2006 2007 2008 2009 2011 2013 2015

% o

f re

spondents

off

eri

ng p

recis

ion

serv

ices

makin

g a

pro

fit

Soil Sampling

Single Variable Rate Application

Multi Variable Rate Application

Satellite Imagery

Yield Monitor Data Analysis

Total Precision Package

2015 Base: 261

Erickson & Widmar, 2015

Page 10: Big data implications - Terry Griffin - 6
Page 11: Big data implications - Terry Griffin - 6

Privacy and Security

• Privacy not a new idea

• “Security” & “privacy”

– Prevent others accessing data

– Prevent data becoming corrupted

– Prevent data loss

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Source: https://www.google.com/trends/

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Source: https://www.google.com/trends/

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Thinking about Farm Data

• Data is intangible and irreplaceable

– “non-rival”

– “Excludable” and/or “non-excludable”

• Copies of digital data identical to original

• Anonymity does not exist with big data

• Value lies in its use, not in the possession

– Data tombs are common (and worthless)

– ‘data has no value’

My Favorite Movie

My Favorite Movie

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Ownership framework

• First: what does it mean to “own” something?– Right to POSSESS*

– Right to USE

– Right to ENJOY

– Right to EXCLUDE OTHERS FROM*

– Right to TRANSFER

– Right to CONSUME or DESTROY*

• Better question: What recourse do people have with respect to misappropriated data?

Stolen from: Shannon Ferrell, Oklahoma State University

[email protected]

Page 16: Big data implications - Terry Griffin - 6

Framework for intangible property

• Where does farm data fit, if at all?

• Intellectual property

– Trademark

– Patent

– Copyright

– Trade secret

• Ellixson & Griffin, 2017 U.S. Const. Art. I, §8, c. 8

Stolen from: Shannon Ferrell, Oklahoma State University

[email protected]

Page 17: Big data implications - Terry Griffin - 6

Community Data Analysis

• Community Participation: Value to Farmer vs Network

• Value of primary use < value of secondary use

Image credit: Fox Photos/Getty Images

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Data Primary Use Secondary Use

Yield monitor data Documenting yields

On-farm trials

Splitting crop shares

GxExM analyses

Soil sample data Fertilizer decisions Regional compliance

Algorithm development

Scouting Spray decisions Regional analytics

Early alerts

As-applied fertility On-farm trials

Compliance

Algorithm development

Single Field vs Community

Are value of secondary uses > primary uses?

Need 1 field Need many fields

Page 19: Big data implications - Terry Griffin - 6

Farm Data as Intangible Resource

• Reluctant to share data

• Ramification of relinquishing control?– Gives up bargaining power

– Fear own data used against them

Source: Shanoyan and Griffin

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Valuation of Precision Ag Data• Consider the farm-level value of ‘lost data’

– Pirate holding data for ransom

– Willingness-to-pay for data security

• Spoiler: typically low compared to collection effort

• Court system likely decide value

– Rather than free market

Farm Data Valuation

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0

5

10

15

20

25

30

2010 2015

Mbit

per

second

Are FCC-Defined Broadband Speed Enough?

down up

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Broadband Speeds Enough?

• UAV imagery example (Buschermohle, U of Tennessee)

– 40 acre field with 17 pictures ~ 111 MB (almost 3 MB/acre)

– 92 acres with 152 pictures ~ 450MB (almost 5 MB/acre)

• Other sensor and prescription data (Shearer, tOSU)

– Spraying 0.3 MB/acre

– Planting 5.5 MB/acre

– Yield data 4.2 MB/acre

– Soil/Fertility Data 0.6 MB/acre

– Prescription files 0.01 MB/acre 0

10

20

30

2010 2015M

bit

per

second

down up

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FCC Broadband Definition: 2010 to 2014

Source: http://www.broadbandmap.gov/speed

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FCC Broadband Definition: 2015

Source: http://www.broadbandmap.gov/speed

Page 25: Big data implications - Terry Griffin - 6

Farm Data Quality

• Yield monitor data is great, but…

– Sensor calibration crucial

– Yield cleaning necessary

– Data ≠ truth

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USDA ARS Yield Editor

Raw data from combine yield monitor

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Default cleaning algorithm

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Advanced data cleaning algorithm

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Opportunities

Stolen from: Shannon Ferrell

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“Future” of Farm Data

• Wireless infrastructure impacts farmland values

• Secondary uses recognized as valuable

– If yield monitor malfunctions, harvester stops for repair

• Data quality viewed as important

– Small data at the grower:farm:field level

– Big data at the community level

• Going off grid not sustainable

Page 31: Big data implications - Terry Griffin - 6

Acknowledgements

Dr. Shannon L. Ferrell

Associate Professor, Agricultural Law

Dept. of Agricultural Economics

Oklahoma State University

Dr. Aleksan Shanoyan

Assistant Professor

Department of Agricultural Economics

Kansas State University

Terry Griffin

Cropping Systems Economist

[email protected]

501.249.6360

@SpacePlowboy


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