The document presents a case study of a coopetitive data warehouse created for AOPUnoLombardia, an organization of fruit and vegetable producers in Italy. A methodology is introduced for designing information systems that allow both cooperation and competition between firms by controlling access to sensitive shared data. The system was evaluated based on its use by AOPUnoLombardia to analyze reductions in sales and raw materials purchases during an E. coli outbreak in 2011. Future work is planned to expand the system to more grower organizations and the Lombardy orchard industry.

1. Coopetitive Data Warehouse:
a case study
Andrea Maurino, Claudio Venturini, Gianluigi Viscusi
DISCo - Dip. di Informatica, Sistematica e Comunicazione
Università di Milano Bicocca
viale Sarca 336/14,
20124, Milano (Italy)

2. Index
• The problem
• Co-opetition, who are you?
• Theoretical background
• A methodology for designing coopetitive
information systems
• The AOPUnoLombardia case study
• Evaluation
• Conclusion and future work
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3. The problem
• In each market firms are always in competition
• But, sometime, they need to be aggregated
• Law imposes or encourages such aggregation (lobbying,
founding)
• better understand the market
• Thus firms sometime need to cooperate
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4. Co-opetition, who are you?
• Coopetition is a kind of relationship in which firms
show competition and cooperation behaviours
• Very well studied in economy
• NOT STUDIED IN ICT!
• We studied the problem of designing a coopetitive
datawarehouse where firms share their sensitive
data
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5. Theoretical background
• Coopetition can be modelled whit game theory
• Let
• A, B two firms
• {(S) share – (NS) no share} possibile decision
• Ka and Kb amount of shared knowledge
• Lv is the loss value due to share information with others
• Av is the added value to have information from others
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6. Theoretical background
• Share, share is a dominant solution for a company
x if
• Kx-Lv+Av>Kx 
• How to measure Av and Lv? (any idea?)
• But in Lv is relied on
• Access
• Trust
• Privacy
• Quality
• We reduce the value of Lv
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7. Theoretical background
• Access control policies;
• Extraction of data from organizations
• Integration and load into the DW
• Presentation of results
• Trust
• If you want to freely join in an organization you
trust in it!
• Privacy preserving strategies
• Quality of shared data.
• Reduced quality  reduced value of information
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8. The architecture
• GVV is a global virtual view integrating existing
schema
• Data are still in whithin firm borders and they are queried
when needed
• It is a virtual operational data store
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• When ETL asks for
data they are
queried by the
GVV to firms,
intregrated on the
fly and stored in
DW
• Anonymous

9. The methodology
• 2 phases requirement
• Concept definition
• Aggrement among firms on
WHAT Dw will mange data
• Definition of the global
model
• Quality of exposed data
• Data aggregation
• Concepts classification
• Aggrement among firms on
HOW Dw will manage data
• Mandatory Access
control
• 5 security levels
• Unclassified,
classifed, confident,
secret and top secret
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10. The methodology
• 1. unclassified: concept X can be shared freely.
• 2. classified: plain concept X can be shared with a
intermediated quality level
• 3. confidential: concept X can be shared in an
aggregate way with a intermediate quality level.
• 4. secret: concept X can be shared, in a way to
preserve privacy, and with a
• low level quality.
• 5. top secret: concept X must not be accessed.
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11. The methodology
• How reduce quality of data?
• Reduce
• Accuracy
• Completeness
• Consistency
• Time related
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Also for antitrust law…

12. The AOPUnoLombardia case
• AOP UnoLombardia is an organization of fruit and
vegetable producers.
• 13 grower organizations (GO) including
• Bonduelle and Dimmidisi.
• It represents about the 30% of the whole fruit and
vegetables market in Italy.
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13. The AOPUnoLombardia case
• AOP UnoLombardia wanted to develop a coopetitive
data warehouse for the following goals:
• to obtain a unified analysis of selling of goods in term of
price and amount of sold pieces
• to obtain a unified view of raw materials bought
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14. The AopUnoLombardia case
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15. Evaluation
• May 2011 E.coli bacteria outbreak
• No deads in Italy at all!
• Anyway …PANIC!
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16. Evaluation
• AOPUnoLombardia use our system to evaluate
• the reduction of the amount of product type sold to large-
scale retail wrt the the previous year
• the reduction of purchase of raw material wrt the the
previous year
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- Average reduction of sold products is
about 29%
-In some case the number of sold
product was reduced by a 38%
-only in September 2011 the amount of
sold items had the same value of
the previous year.
-while the amount of brought salad is
more or less the same!
due to preexisting aggreements

17. Conclusion and future works
• Coopetition is a kind or relationships in which firms
show a cooperative and coopetitive behaviours
• The problem of building a coopetitive informatiom
system is a new problem!
• We started by design and impement a coopetitive
datawarehouse
• Applied to AOPUnoLombardia case study
• Future Work
• From a theoretical view point a better definition of
information value
• We are currenting extend our system to include other GOs
• We are studing how to apply our system in the ortofruit
district in Lombardia including seeding and tools producing
firms
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18. Thanks!
疑问
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