A Metamodel for Supporting Interoperability in Heterogeneous Ontology Networks

  • Rodrigo BonacinEmail author
  • Ivo Calado
  • Julio Cesar dos Reis
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 527)


Ontologies are central artifacts in modern information systems. Ontology networks consider the coexistence of different ontology models in the same conceptual space. It is relevant that computational systems specified with distinct models based on different methods, as well as divergent metaphysical assumptions, exchange data to interoperate one with the other. However, there is a lack of techniques to enable the adequate conciliation among models. In this paper, we propose and formalize a metamodel to enable the construction of data models aiming to support the interoperability at the technical level. We present the use of our metamodel to conciliate, without explicit transformations, Ontology Charts from Organizational Semiotics with Semantic Web OWL ontologies and less structured models such as soft ontologies. Our results indicate the possibility of identifying an entity from one model into another, enabling data exchange and interpretation in heterogeneous ontology network.


Ontology Chart OWL ontologies Soft ontologies Metamodeling 



This work is supported by the São Paulo Research Foundation (FAPESP) (Grants #2015/16528-0 and #2017/02325-5).


  1. 1.
    Ades, Y., Umar, F.B., Poernomo, I., Tsaramirsis, G.: Mapping ontology charts to UML: an SNF preserving transformation. In: Proceedings of the 10th International Conference on Organisational Semiotics (2007)Google Scholar
  2. 2.
    Bonacin, R., Baranauskas, M.C.C., Liu, K.: From ontology charts to class diagrams: semantic analysis aiding systems design. In: 6th International Conference on Enterprise Information Systems (ICEIS 2004), pp. 389–395 (2004)Google Scholar
  3. 3.
    Dos Reis, J.C., Bonacin, R., Baranauskas, M.C.C.: A semiotic-based approach to the design of web ontologies. In: 12th International Conference on Informatics and Semiotics in Organisations (ICISO 2010), pp. 60–67 (2010)Google Scholar
  4. 4.
    Dos Reis, J.C., Bonacin, R., Baranauskas, M.C.C.: An assisted process for building semiotic web ontology. In: 13th International Conference on Informatics and Semiotics in Organisations (ICISO 2011), pp. 167–174 (2011)Google Scholar
  5. 5.
    Dos Reis, J.C., Bonacin, R., Baranauskas, M.C.C.: Constructing web ontologies informed by semantic analysis method. In: 13th International Conference on Enterprise Information Systems (ICEIS 2011), pp. 203–206 (2011)Google Scholar
  6. 6.
    Gibson, J.J.: The theory of affordances. In: Perceiving, Acting, and Knowing: Towards an Ecological Psychology. Wiley, Hoboken (1977)Google Scholar
  7. 7.
    Gruber, T.R.: Toward principles for the design of ontologies used for knowledge sharing. Int. J. Hum. Comput. Stud. 43(5–6), 907–928 (1995)CrossRefGoogle Scholar
  8. 8.
    Kaipainen, M., Normak, P., Niglas, K., Kippar, J., Laanpere, M.: Soft ontologies, spatial representations and multi-perspective explorability. Expert Syst. 25(5), 474–483 (2008)CrossRefGoogle Scholar
  9. 9.
    Kalyanpur, A., Golbeck, J., Banerjee, J., Hendler, J.: Owl: capturing semantic information using a standardized web ontology language. Multiling. Comput. Technol. Mag. 15(7) (2004)Google Scholar
  10. 10.
    Liu, K., Li, W.: Organisational Semiotics for Business Informatics. Routledge, Abingdon (2014)Google Scholar
  11. 11.
    Lv, Y., Ma, Z.M., Yan, L.: Fuzzy RDF: a data model to represent fuzzy metadata. In: IEEE International Conference on Fuzzy Systems. IEEE World Congress on Computational Intelligence, pp. 1439–1445 (2008)Google Scholar
  12. 12.
    Nguyen, N.T., Truong, H.B.: A consensus-based method for fuzzy ontology integration. In: Pan, J.-S., Chen, S.-M., Nguyen, N.T. (eds.) ICCCI 2010. LNCS (LNAI), vol. 6422, pp. 480–489. Springer, Heidelberg (2010). Scholar
  13. 13.
    Salter, A; Liu, K.: Using semantic analysis and norm analysis to model organisations. In: Proceedings of the 4th ICEIS, pp. 847–850 (2002)Google Scholar
  14. 14.
    Santos, T.M.D., Bonacin, R., Baranauskas, M.C.C., Rodrigues, M.A.: A model driven architecture tool based on semantic analysis method. In: Proceedings of the ICEIS, pp. 305–310 (2008)Google Scholar
  15. 15.
    Stamper, R., Liu, K., Sun, L., Tan, S., Shah, H., Sharp, B., Dong, D.: Semiotic methods for enterprise design and it applications. In: Proceedings of the 7th International Workshop on Organisational Semiotics (OS) (2004)Google Scholar
  16. 16.
    Timm, J.T.E., Gannod, G.C.: A model-driven approach for specifying semantic web services. In: International Conference on Web Services, pp. 313–320 (2005)Google Scholar
  17. 17.
    Umer, Q., Mundy, D.: Semantically intelligent semi-automated ontology integration. In: Proceedings of the World Congress on Engineering (2012)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  • Rodrigo Bonacin
    • 1
    • 2
    Email author
  • Ivo Calado
    • 3
  • Julio Cesar dos Reis
    • 4
  1. 1.UNIFACCAMPCampo Limpo PaulistaBrazil
  2. 2.CTICampinasBrazil
  3. 3.Federal Institute of AlagoasRio LargoBrazil
  4. 4.Institute of Computing, UNICAMPCampinasBrazil

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