Data Ownership Aspects in

the Agricultural Production

Environment

Ralph Ostermeier, Christian Bartolein, Georg Kormann

January 26th, VDI Seminar Landtechnik, Weihenstephan

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Content

• Motivation

• iGreen Research Project

• Data Management Approach

• Data Ownership Aspects

• Conclusion

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Advancing Technology drives Agriculture

Public information as well as product and expert knowledge are increasingly digitized and available via the internet, such as different kinds of maps and weather data.

Accessing the internet is possible from almost all locations via mobile devices. GPS devices for positioning are easy to buy or are even part of mobile phones.

Agricultural engineering provides more and more software interfaces for automatic situation-adaptive control (machine terminals, sensor technology, …).

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Integration of location-based Data is Key to Knowledge Management in Agriculture

Public geo data are a valuable basis for location-specific services

Mobile access to data, knowledge sources, and services enables effective support on site

Combination of public and private actors facilitates comprehensive and efficient services

• Improved consulting combining public data and private services

• Enhanced data quality by exploiting individual sensors

iGreen Research Project

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iGreen Objectives

• Research to enable intelligent and seamless data and knowledge sharing around agricultural production environment.

• Combine public and private information sources from decentralized locations.

• Connection of vehicles, mobile devices and back-office systems using standardized and open communication protocols.

• Development of demonstrators to prove feasibility.

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Project Consortium

private public

Connectivity

Management Consulting services

(international) (national) (regional)

Interests of the social community Interests of the agricultural sector

EPP

e.v .

(nationwide) iis

Farmers / agricultural service supply agency © 2011 DFKI &

iGreen Consortium

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iGreen is Funded by the BMBF in Frame of the IKT 2020 Initiative

• Project duration April 2009 – December 2012

• Approved budget 23.144.000 €

• Total funding 14.228.000 €

• Avg. funding rate 61%

• Project homepage www.igreen-projekt.de

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iGreen Data Management Infrastructure

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Scenario 1: Farm owner is machine owner

Governmental Reporting / Public Resources

John Deere Dealer/ Customer Support

Farm Office

• System Frontend • Initiates Data exchange to partners

Farmer’s Data Ownership Sphere

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Scenario 2: Contractor operates leased machine in neighboring country

Governmental Reporting / Public Resources

John Deere Dealer/ Customer Support

Farm Office

• FMIS • Data Frontend to online-hosted data

Machine Owner’s Data Ownership Sphere

Data Hosting Service

•Collecting Data •Hosting Data •Providing Access

Contractor IT system

• Order handling • Task planning and logistics • Billing

Contractor’s Data Ownership Sphere

Farmer’s Data Ownership Sphere

Located in France

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Data Ownership Implications

1. Contractor leases machine from leasing company

• Who owns/gets access to machine-related data?

• How must data being recorded by machine be handled?

2. Contractor harvests fields of a customer in France (field might be rent from owner)

• How is field-, customer-, and driver-related data to be handled?

• Which country-specific legal requirements exist?

3. Data is stored at hosting service

• Where is hosting located/Which country-specific rules do apply?

• How can secure access to online data be ensured?

4. Subsets of data shall be shared with a) Dealer

b) Consultant

c) Ag Machinery Manufacturer

d) etc.

Data Ownership

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iGreen Task Force „Data Ownership“

Objective: Evaluation of legal aspects of capturing, storing, and exchanging data during agricultural production and business processes

Team: DFKI, CLAAS, CCI, Amazone, John Deere, BLU, DLR-RNH

Tasks

• Definition of relevant data types

• Identification of groups of ownership to be considered

• Capturing of relevant legal regulations at federal state, national, and EU levels

• Investigation of technical solutions allowing for data capturing, storage, and exchange and related legal implications

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iGreen Task Force „Data Ownership“

Goals

• Analysis of legal requirements concerning data handling for iGreen scenarios, mainly based on Federal Data Protection Law (BDSG)

• Define needs for data capturing

• Develop proposals for usage agreements, access rights and roles

• Trigger technical discussions and make proposals on how to solve encountered challenges

Limitations

• No legal person permanently on the team

• Team members are consulting with their legal departments

• iGreen can not give final legal advise

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Relevant Roles regarding Data Ownership

• Machine owner

• Machine operator

• Farmer

• Land owner

• Gov. agency

• Laboratory

• Farm manager

• Legal instance

• Tariff partner

• Service provider

• Consultant

• Accident Prevention & Insurance Association (Berufsgenossenschaft)

• Social insurance carrier

• Contractor

• Client

• Machinery manufacturer

• Field-neighbor

• etc.

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Relevant Data Types

Person-related

• Name

• Working hours

• Locations

• Authorizations, permissions, licenses

• Contracts

• Tasks

• Occupational health and safety

• Process knowledge and IP

• Payment

• Absenteeism

• …

Machine/System-related

• Tasks

• GPS position of vehicle

• Yield & quality data

• Application supplements & rates

• Fields and boundaries

• Process restrictions

• Water protection zones

• Soil quality

• Usage limitations

• Contracts, business relationships

• Machine data

• …

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Technical and Organizational Aspects

Considerations for physical data storage

• Storage location: Inside/outside country

• Local server storage vs. cloud-based approaches

• Data security and backup concepts

Technical Measures

• Removal of personal relation by anonymization, using aliases, aggregation, pre-processing, deletion after deadline, tracking, hashing, etc.

• Data Encryption e.g. via public/private keys or symmetric encryption

• Applying digital signatures to increase trust in data and documents

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Expected Outcomes

• Checklist with aspects to be considered

• Templates for process steps to be followed, e.g. getting customer

agreement for data storage/usage

• List of encountered typical data ownership issues

• FAQ regarding data ownership in agriculture

iGreen Task Force can not provide legally binding documents

Project partners will use outcomes as input for creation of

individual contracts and agreements

Conclusion

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Conclusion

• Enabling agricultural stakeholders to provide services to each

other requires extensive storage and sharing of data

• Technology and solutions for comprehensive storage and

exchange of agricultural data start to be available

• Data ownership aspects have to be covered in parallel

• Technical measures to make data sharing conform to legal

requirements exist

• Research project iGreen provides opportunity to collaboratively investigate data ownership aspects in agriculture and to develop a common understanding