13th International Conference on Enterprise Information Systems, ICEIS’2011, June 8-11, 2011, Beijing, P.R. China

1. Local Ontologies for Semantic Interoperability in Supply Chain Networks Milan Zdravković, Miroslav Trajanović University of Niš, Serbia milan.zdravkovic@masfak.ni.ac.rs, traja@masfak.ni.ac.rs Hervé Panetto Research Centre for Automatic Control (CRAN – UMR 7039), Nancy-Université, CNRS, France [email_address] ICEIS’2011, June 8-11, 2011, Beijing, P.R. China

3. Virtual organizations – Supply chains of the future ? *Virtual Breeding Environment Ent 2 Ent 4 Ent 1 Ent 3 Ent 5 Ent 6 **Virtual Enterprise 1 Ent 21 Ent 41 Ent 11 Ent 31 Ent 61 **Virtual Enterprise n Ent 2n Ent 4n Ent 5n Ent 3n Opportunity 1 Opportunity n Selection Configuration Selection Configuration Dissolution Dissolution **Temporary network of independent enterprises, who join together quickly to exploit fast-changing opportunities and then dissolve (Browne and Zhang, 1999) * Pool of organizations and related supporting institutions that have both the potential and the will to cooperate with each other through the establishment of a “base” long-term cooperation agreement and interoperable infrastructure . (Sánchez et al, 2005)

5. Is it easy ? English translation of Welsh: “I am not in the office at the moment. Please send any work to be translated”

9. Our approach to semantic interoperability in supply chain networks 2/2 SCOR- MAP SCOR-FULL OWL SCOR-SYS OWL SCOR-KOS OWL SCOR Native formats, Exchange formats Domain Ontologies Implicit semantics Explicit semantics Semantic enrichment Formal models of design goals Semantic applications Enterprise Information Systems SCOR-based systems SCOR-CFG OWL SCOR-GOAL OWL PRODUCT OWL Semantic Query service EIS database LOCAL ONTOLOGY Transformation service EIS database LOCAL ONTOLOGY EIS database LOCAL ONTOLOGY

11. Our approach to database-to-ontology mapping Database 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

17. Local Ontologies for Semantic Interoperability in Supply Chain Networks Milan Zdravković, Miroslav Trajanović University of Niš, Serbia milan.zdravkovic@masfak.ni.ac.rs, traja@masfak.ni.ac.rs Hervé Panetto Research Centre for Automatic Control (CRAN – UMR 7039), Nancy-Université, CNRS, France [email_address] ICEIS’2011, June 8-11, 2011, Beijing, P.R. China Thank you for your attention