YEAR 4 HIGHLIGHTS€¦ · RUC-APS YEAR 4 HIGHLIGHTS Interoperability Assessment (Ford et al.,...

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RUC-APS YEAR 4 HIGHLIGHTS Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems (RUC-APS) WP Leader Prof. Hervé Panetto Université de Lorraine, CRAN, CNRS, France [email protected] WP 11 Enterprise systems interoperability assessment in Agriculture domains YEAR 4 HIGHLIGHTS Skype for Business: https://meet.lync.com/univ-lorraine.fr/panetto5/XAXC6HFI The session is recorded!

Transcript of YEAR 4 HIGHLIGHTS€¦ · RUC-APS YEAR 4 HIGHLIGHTS Interoperability Assessment (Ford et al.,...

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RUC-APS YEAR 4 HIGHLIGHTS

Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems

(RUC-APS)

WP Leader

Prof. Hervé Panetto

Université de Lorraine, CRAN, CNRS, France

[email protected]

WP 11

Enterprise systems interoperability assessment

in Agriculture domains

YEAR 4 HIGHLIGHTS

Skype for Business: https://meet.lync.com/univ-lorraine.fr/panetto5/XAXC6HFI

The session is recorded!

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THE WP11 TEAM at ULName Institution/Group Expertise

Prof. Hervé Panetto (WP Leader) UL/CRAN Interoperability of systems, cyber-physical systems

Dr. Mario Lezoche UL/CRAN Knowledge management and ontology

Dr. William Dérigent UL/CRAN Data management and BIM

Prof. Hind EL-Haouzi UL/CRAN Simulation-based decision making

Dr. Concetta Semeraro UL/CRAN & POLIBA Data mining and digital twin

Dr. Wided Guédria LIST/CRAN Interoperability assessment

Dr. Gabriel Leal UL/CRAN & LIST Ontology-based interoperability requirements

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Final product

Assessment

info

info

info

info

info

info

info informationcompetencies

products

Problems

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Towards an Interoperabilty Agri-food 4.0Assessment tool

• Generaly interoperable by design

• Human centred

• Technology oriented (CPS, Sensors, AI, …)

• Data, Information and Knowledge –based

• Along the global value chain

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Interoperability Assessment

(Ford et al., 2007a), (Panetto. 2007), (Yahia et al. 2012), (Guédria et al. 2015)

Potent ia l i ty

The potential of an enterprise to

be interoperable towards its

environment

Compat ibi l i ty

The compatibility

Between two

Enterprises

Performance

The performance of

interoperation between

two enterprises

T rans format ion

Identifying impacts that

changes may cause

Creat ion o f a network

Selecting new

partners

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The Conceptual Model: Assessment MetaModel

Systemic coreAssessment core

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The Conceptual Model: Interoperability Assessment MetaModel

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The Conceptual Model: Instantiation

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The Ontology of Interoperability Assessment (OIA)

Protégé 5.2 (Musen, 2015)Extract of the ontology

pointsOutProblem

recommends

removesProblem

satisfies

isSatisfiedBy

mayCause

requires

impactsisRequiredB

y

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Prototyping the computer-mediated tool for Interoperability Assessment in Agriculture

It provides user interfaces

It automatically identifies barriers based

on the requirement rating

It recommends solutions based on:

- the identified barriers

- the knowledge that has been

stored in the OIA

The prototype architecture

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Prototyping the computer-mediated tool forInteroperability Assessment

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Prototyping the computer-mediated tool forInteroperability AssessmentInserting logic rules for automatic reasoning

Language Description (Formula)

Natural

Language:

If a specific requirement that is verified by the assessment has a lower rate than the one

stipulated as “minimum”, the assessment points out the interoperability barrier(s) and

recommends the best practice(s) that are related to the concerned requirement.

SWRL

Language:

Assessment_Process(?iap) ^ Evaluation_Criterion(?ir) ^

verifiesCriterion(?iap, ?ir)^ Existence_Condition(?ib) ^

relatedToCondition (?ir, ?ib) ^ Solution(?bp) ^ satisfiesRequirement(?bp,

?ir) ^ hasRate(?ir, ?ra) ^ hasMin(FA, ?miv) ^ swrlb:lessThan(?ra, ?miv)

-> pointsOutCondition (?iap, ?ib) ^ hasCause(?ib, ?ir) ^ recommends(?iap,

?bp)

Language Description (Formula)

Natural

Language:

If a considered requirement has a rate greater than the stipulated minimum, the

concerned requirement satisfies the related maturity level.

SWRL

Language:

hasMin(FA, ?miv) ^ Quality(?il) ^ dependsOnRequirement(?il, ?ir) ^

Evaluation_Criterion(?ir) ^ hasRate(?ir, ?ra) ^ swrlb:greaterThan(?ra,

?miv) -> satisfiesLevel(?ir, ?il)

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Ontology before reasoning

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Ontology after reasoning

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The case study

The Factory Group

Agrifood productor & supplier

Exxus

Farm

Agro-Interact

Transport

RIDL

Distributor

Sustain

Quality control service

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The Factory Group Case Study20

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DEMONSTRATION

Interoperabilty Agri-food 4.0 Assessment tool

Developed by Gabriel Leal SerapiãoDecision Support for Interoperability readiness analysis in Networked Enterprises. Phdthesis of Université de Lorraine, 2019

Gabriel Leal, Wided Guedria, Hervé Panetto. A semi-automated system for interoperability assessment: an ontology-based approach. Enterprise Information Systems, Taylor & Francis, 2020, 14 (3), pp.308-333. ⟨10.1080/17517575.2019.1678767⟩

The names of the enterprises used in this demo are purely fiction

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Learning Outcomes• Analysis of data sharing and exchange in the food supply chain

• Starting point analysis of applications used in agribusiness

• Information flows between Agrifood stakeholders

• Some idea about the definition of an Agri-Ontology

• The Agri-Food Experiment Ontology (AFEO)

• Interoperability map between enterprise systems in agriculture domain

• Adaptation of the PLATINE prototype for an Ontology-based Interoperability assessment in Agriculture (Demo)

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THANKYOU !Q&A

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RUC-APS YEAR 4 HIGHLIGHTS

Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems

(RUC-APS)

YEAR 4 HIGHLIGHTS

Skype for Business: https://meet.lync.com/univ-lorraine.fr/panetto5/XAXC6HFI

Presenter

Ass. Prof. Mario Lezoche

Université de Lorraine, CRAN, CNRS, France

[email protected]

Next presentation: Wednesday 27th, 2020 – 15:30 CET

Agriculture Ontology