A Reuse-Based Lightweight Method for Developing Linked Data Ontologies and Vocabularies

  • María Poveda-Villalón
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7295)


The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies for describing different domains. Particular LD development characteristics such as agility and web-based architecture necessitate the revision, adaption, and lightening of existing methodologies for ontology development. This thesis proposes a lightweight method for ontology development in an LD context which will be based in data-driven agile developments, existing resources to be reused, and the evaluation of the obtained products considering both classical ontological engineering principles and LD characteristics.


ontology vocabulary methodology linked data 


  1. 1.
    Auer, S.: RapidOWL - an Agile Knowledge Engineering Methodology. In: STICA 2006, Manchester, UK (2006)Google Scholar
  2. 2.
    Fernández-López, M., Gómez-Pérez, A., Juristo, N.: METHONTOLOGY: From Ontological Art Towards Ontological Engineering. In: Spring Symposium on Ontological Engineering of AAAI, pp. 33–40. Stanford University, California (1997)Google Scholar
  3. 3.
    Gómez-Pérez, A., Fernández-López, M., Corcho, O.: Ontological Engineering. Advanced Information and Knowledge Processing. Springer (November 2003) ISBN 1-85233-551-3Google Scholar
  4. 4.
    Gruninger, M., Fox, M.S.: The role of competency questions in enterprise engineering. In: Proceedings of the IFIP WG5.7 Workshop on Benchmarking - Theory and Practice, Trondheim, Norway (1994)Google Scholar
  5. 5.
    Heath, T., Bizer, C.: Linked data: Evolving the Web into a global data space, 1st edn. Morgan & Claypool (2011)Google Scholar
  6. 6.
    Hristozova, M., Sterling, L.: An eXtreme Method for Developing Lightweight Ontologies. CEUR Workshop Series (2002)Google Scholar
  7. 7.
    Pinto, H.S., Tempich, C., Staab, S.: DILIGENT: Towards a fine-grained methodology for DIstributed, Loosely-controlled and evolvInG Engineering of oNTologies. In: de Mantaras, R.L., Saitta, L. (eds.) Proceedings of the ECAI 2004, August 22-27, pp. 393–397. IOS Press, Valencia (2004) ISBN: 1-58603-452-9, ISSN: 0922-6389Google Scholar
  8. 8.
    Presutti, V., Daga, E., Gangemi, A., Blomqvist, E.: eXtreme Design with Content Ontology Design Patterns. In: WOP 2009 (2009)Google Scholar
  9. 9.
    Staab, S., Schnurr, H.P., Studer, R., Sure, Y.: Knowledge Processes and Ontologies. IEEE Intelligent Systems 16(1), 26–34 (2001)CrossRefGoogle Scholar
  10. 10.
    Suárez-Figueroa, M.C.: Doctoral Thesis: NeOn Methodology for Building Ontology Networks: Specification, Scheduling and Reuse. Universidad Politécnica de Madrid, Spain (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • María Poveda-Villalón
    • 1
  1. 1.Ontology Engineering Group. Departamento de Inteligencia Artificial, Facultad de InformáticaUniversidad Politécnica de MadridBoadilla del MonteSpain

Personalised recommendations