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Towards Semantic Interoperability Service Utilities Milan Zdravkovi ć , Miroslav Trajanovi ć Laboratory for Intelligent Production Systems (LIPS) Faculty of Mechanical Engineering, University of Ni š, Serbia 6th International Workshop on Enterprise Integration, Interoperability and Networking (EI2N), 19-21 October, 2011, Herssonisos, Greece
Human communication as a raw model for interoperability Sensation Perception Cognition Articulation Selection of sensations Providing meaning to various sensations In contexts of expectations, experience, culture, etc. Gaining knowledge and comprehension from the sensations Storage, reasoning, problem solving, imagining, conceptualizing Stimulus sensory energy psysiological psychological Articulating response Receipients, language, means
Requirements for semantic interoperability ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],∃ S(system(S)) ∀ p ( (transmitted-from(p,S) ∧ transmitted-to(p,R)) ∧  ∀ q(statement-of(q,S) ∧ p⇒q)  ∃ q’(statement-of(q’,R) ∧ p⇒q’ ∧ q’⇔q) ) ⇒  semantically-interoperable(S,R) Sensation Perception Cognition Articulation ∃ R(system(R)) Sensation Perception Cognition Articulation Web services Ontologies Query processing Semantic matching Reasoner Ontologies Mappings
Implicit semantics Explicit semantics Semantic applications and services Enterprise Information Systems S-ISU for Semantically interoperable systems MAPPING ONTOLOGY PROB ONT PROB ONT Transformation service LOCAL ONTOLOGY LOCAL ONTOLOGY DOMAIN ONT DOMAIN ONT DOMAIN ONT Native formats, Exchange formats EIS database EIS database Semantic Query service Listener Listener Reasoning service Registration service Reconciliation service
Component view of S-ISU architecture ONTOLOGY Main Services EIS LOCAL CENTRAL UTILITY EIS Database Listener Local Ontology Native formats Exchange formats Local Ontology Local Ontology Mapping Ontology DomOnt 1 DomOnt n ProbOnt 1 ProbOnt m Supportive Apps Semantic Apps VE formation Services SQS ReaS RegS SRS TrS RegSApp SRSApp SemApp 1 SemApp n } } AuthApp ReaS
S-ISU Services ,[object Object],[object Object],[object Object],[object Object],[object Object]
Database-to-ontology mapping Database Zdravković, M., Trajanović, M. & Panetto, H., 2011.  LOCAL ONTOLOGIES FOR SEMANTIC INTEROPERABILITY IN SUPPLY CHAIN NETWORKS . In  Proceedings of the 13th International Conference on Enterprise Information Systems (ICEIS 2011) . SciTePress - Science and and Technology Publications, pp. 22-31.   er.owl attribute constraint entity multiplicity relation type hasAttribute hasType hasConstraint hasSourceAttribute hasDestinationAttribute hasSourceMultiplicity hasDestinationMultiplicity output imports s-er.owl concept hasObjectProperty data-type hasDataProperty data-concept hasDataType hasDefiningProperty hasDefiningDataProperty hasFunctionalProperty output er:entity(x) ∧ not (er:hasAttribute only (er:attribute ∧ (er:isSourceAttributeOf some er:relation))) ⇒  s-er:concept(x) er:entity(x) ∧ er:entity(y) ∧ er:relation(r) ∧ er:hasAttribute(x, a1) ∧ er:hasAttribute(y, a2) ∧ er:isDestinationAttributeOf(a2, r) ∧ er:isSourceAttributeOf(a1, r) ⇒  s-er:hasObjectProperty(x, y) s-er:hasObjectProperty(x, y) ∧ er:hasConstraint(a1,'not-null') ⇒  s-er:hasDefiningProperty(x, y) er:attribute and not (er:isSourceAttributeOf some er:relation) ⇒  s-er:data-concept er:type(x) ⇒  s-er:data-type(x) s-er:concept(c) ∧ er:attribute(a) ∧ er:type(t) ∧ er:hasAttribute(c, a) ∧ er:hasType(a, t) ⇒  s-er:hasDataProperty(c, t) s-er:hasDataProperty(c, t) ∧ er:hasConstraint(a,'not-null') ∧ er:hasConstraint(a,'unique') ⇒  s-er:hasDefiningDataProperty(c, t) Data import and classification of ER entities Classification (inference) of  OWL types and properties Lexical Refinement Local ontology generation output
Formalizing the S-ISU Architecture S-ISU Ontology Meta-information for Registration Utility Inference of the basic system properties MDE paradigm
has-process process-snow-making-manufacturing-1 process-pump-house-sourcing-1 VBE Utility Enterprise Process VE has-member owns-utility facilitates precedes implements-process Hydro-Equip-Cluster Snow-making-facility-engineering Snow-Solutions-Inc Pumps-Inc Lenko-Snow-Inc Organizational view of S-ISU ontology (case) Process(p1)∧Process(p2)∧ Enterprise(e1)∧Enterprise(e2)∧ implements-process(e1,p1)∧ implements-process(e2,p2)∧ precedes(p1, p2)∧ DifferentFrom(e1,e2)  ⇒  interoperate-with(e1,e2)  Inferred properties interoperate-with('Pumps-Inc', 'Snow-Solutions-Inc'),  interoperate-with('Lenko-Snow-Inc', 'Snow-Solutions-Inc'),  interoperate-with('Snow-Solutions-Inc', 'Lenko-Snow-Inc'), interoperate-with('Snow-Solutions-Inc', 'Pumps-Inc').  process-pump-house-manufacturing-1 process-fan-gun-sourcing-1 process-hyd-equip-sourcing-1 process-hyd-equip-delivery-1 process-pump-house-delivery-1 process-pump-house-design-1 process-snow-making-design-1 process-fan-gun-delivery-1 process-hyd-equip-manufacturing-1 process-snow-making-delivery-1
Asset view of S-ISU ontology (case) EIS SemApp Database Ontology AppOntology MapOntology DomOntology LocOntology Data-Container File ReaS SQS RegS TrS SRS RegSApp SRSApp uses-utility uses-utility uses-utility uses-utility Utility Service Listener uses-utility ERPNext-1 OpenERP-1 EasySCOR-1 EasySCOR-1-Native ERPNext-1-MySQL OpenERP-1-PostgreSQL SCOR-KOS OWL ERPNext-1-Ont OpenERP-1-Ont explicits explicits explicits imports imports imports uses-data-container uses-data-container uses-data-container TOVE SCOR-MAP SCOR-FULL imports imports imports imports uses-data-container SCOR-Thread-Gen SCOR-CFG PRODUCT-OWL Prod-Acquis-App uses-data-container uses-utility uses-utility
Thank you for your attention Q&A Milan Zdravkovi ć , Miroslav Trajanovi ć Laboratory for Intelligent Production Systems (LIPS) Faculty of Mechanical Engineering, University of Ni š, Serbia 6th International Workshop on Enterprise Integration, Interoperability and Networking (EI2N), 19-21 October, 2011, Herssonisos, Greece

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Towards Semantic Interoperability Service Utilities

  • 1. Towards Semantic Interoperability Service Utilities Milan Zdravkovi ć , Miroslav Trajanovi ć Laboratory for Intelligent Production Systems (LIPS) Faculty of Mechanical Engineering, University of Ni š, Serbia 6th International Workshop on Enterprise Integration, Interoperability and Networking (EI2N), 19-21 October, 2011, Herssonisos, Greece
  • 2. Human communication as a raw model for interoperability Sensation Perception Cognition Articulation Selection of sensations Providing meaning to various sensations In contexts of expectations, experience, culture, etc. Gaining knowledge and comprehension from the sensations Storage, reasoning, problem solving, imagining, conceptualizing Stimulus sensory energy psysiological psychological Articulating response Receipients, language, means
  • 3.
  • 4. Implicit semantics Explicit semantics Semantic applications and services Enterprise Information Systems S-ISU for Semantically interoperable systems MAPPING ONTOLOGY PROB ONT PROB ONT Transformation service LOCAL ONTOLOGY LOCAL ONTOLOGY DOMAIN ONT DOMAIN ONT DOMAIN ONT Native formats, Exchange formats EIS database EIS database Semantic Query service Listener Listener Reasoning service Registration service Reconciliation service
  • 5. Component view of S-ISU architecture ONTOLOGY Main Services EIS LOCAL CENTRAL UTILITY EIS Database Listener Local Ontology Native formats Exchange formats Local Ontology Local Ontology Mapping Ontology DomOnt 1 DomOnt n ProbOnt 1 ProbOnt m Supportive Apps Semantic Apps VE formation Services SQS ReaS RegS SRS TrS RegSApp SRSApp SemApp 1 SemApp n } } AuthApp ReaS
  • 6.
  • 7. Database-to-ontology mapping Database Zdravković, M., Trajanović, M. & Panetto, H., 2011. LOCAL ONTOLOGIES FOR SEMANTIC INTEROPERABILITY IN SUPPLY CHAIN NETWORKS . In Proceedings of the 13th International Conference on Enterprise Information Systems (ICEIS 2011) . SciTePress - Science and and Technology Publications, pp. 22-31.  er.owl attribute constraint entity multiplicity relation type hasAttribute hasType hasConstraint hasSourceAttribute hasDestinationAttribute hasSourceMultiplicity hasDestinationMultiplicity output imports s-er.owl concept hasObjectProperty data-type hasDataProperty data-concept hasDataType hasDefiningProperty hasDefiningDataProperty hasFunctionalProperty output er:entity(x) ∧ not (er:hasAttribute only (er:attribute ∧ (er:isSourceAttributeOf some er:relation))) ⇒ s-er:concept(x) er:entity(x) ∧ er:entity(y) ∧ er:relation(r) ∧ er:hasAttribute(x, a1) ∧ er:hasAttribute(y, a2) ∧ er:isDestinationAttributeOf(a2, r) ∧ er:isSourceAttributeOf(a1, r) ⇒ s-er:hasObjectProperty(x, y) s-er:hasObjectProperty(x, y) ∧ er:hasConstraint(a1,'not-null') ⇒ s-er:hasDefiningProperty(x, y) er:attribute and not (er:isSourceAttributeOf some er:relation) ⇒ s-er:data-concept er:type(x) ⇒ s-er:data-type(x) s-er:concept(c) ∧ er:attribute(a) ∧ er:type(t) ∧ er:hasAttribute(c, a) ∧ er:hasType(a, t) ⇒ s-er:hasDataProperty(c, t) s-er:hasDataProperty(c, t) ∧ er:hasConstraint(a,'not-null') ∧ er:hasConstraint(a,'unique') ⇒ s-er:hasDefiningDataProperty(c, t) Data import and classification of ER entities Classification (inference) of OWL types and properties Lexical Refinement Local ontology generation output
  • 8. Formalizing the S-ISU Architecture S-ISU Ontology Meta-information for Registration Utility Inference of the basic system properties MDE paradigm
  • 9. has-process process-snow-making-manufacturing-1 process-pump-house-sourcing-1 VBE Utility Enterprise Process VE has-member owns-utility facilitates precedes implements-process Hydro-Equip-Cluster Snow-making-facility-engineering Snow-Solutions-Inc Pumps-Inc Lenko-Snow-Inc Organizational view of S-ISU ontology (case) Process(p1)∧Process(p2)∧ Enterprise(e1)∧Enterprise(e2)∧ implements-process(e1,p1)∧ implements-process(e2,p2)∧ precedes(p1, p2)∧ DifferentFrom(e1,e2) ⇒ interoperate-with(e1,e2) Inferred properties interoperate-with('Pumps-Inc', 'Snow-Solutions-Inc'), interoperate-with('Lenko-Snow-Inc', 'Snow-Solutions-Inc'), interoperate-with('Snow-Solutions-Inc', 'Lenko-Snow-Inc'), interoperate-with('Snow-Solutions-Inc', 'Pumps-Inc'). process-pump-house-manufacturing-1 process-fan-gun-sourcing-1 process-hyd-equip-sourcing-1 process-hyd-equip-delivery-1 process-pump-house-delivery-1 process-pump-house-design-1 process-snow-making-design-1 process-fan-gun-delivery-1 process-hyd-equip-manufacturing-1 process-snow-making-delivery-1
  • 10. Asset view of S-ISU ontology (case) EIS SemApp Database Ontology AppOntology MapOntology DomOntology LocOntology Data-Container File ReaS SQS RegS TrS SRS RegSApp SRSApp uses-utility uses-utility uses-utility uses-utility Utility Service Listener uses-utility ERPNext-1 OpenERP-1 EasySCOR-1 EasySCOR-1-Native ERPNext-1-MySQL OpenERP-1-PostgreSQL SCOR-KOS OWL ERPNext-1-Ont OpenERP-1-Ont explicits explicits explicits imports imports imports uses-data-container uses-data-container uses-data-container TOVE SCOR-MAP SCOR-FULL imports imports imports imports uses-data-container SCOR-Thread-Gen SCOR-CFG PRODUCT-OWL Prod-Acquis-App uses-data-container uses-utility uses-utility
  • 11. Thank you for your attention Q&A Milan Zdravkovi ć , Miroslav Trajanovi ć Laboratory for Intelligent Production Systems (LIPS) Faculty of Mechanical Engineering, University of Ni š, Serbia 6th International Workshop on Enterprise Integration, Interoperability and Networking (EI2N), 19-21 October, 2011, Herssonisos, Greece

Notes de l'éditeur

  1. Common misconception: differences between semantic interoperability an semantically facilitated interoperability.
  2. A sender's system S is _semantically operable_ with a receiver's system R if and only if the follow condition holds for any data p that is transmitted from S to R: For every statement q that is implied by p on the system S, there is a statement q' on the system R that (1) is implied by p on the system R, and (2) is logically equivalent to q. the receiver must at least be able to derive a logically equivalent implication for every implication of the sender's system.
  3. SCOR-MAP is a central ontology. It imports (blue arrows) domain ontologies, implicit SCOR model represented in OWL (SCOR-KOS OWL), SCOR’s semantic enrichment (SCOR-FULL OWL) and all local ontologies. SCOR-MAP stores the SWRL rules which are used to represent correspondences between all these models. Focus of this paper is on what is inside purple boxes.