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Methodologies, Tools and Languages for Ontology Design

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Legal Ontology Engineering

Part of the book series: Law, Governance and Technology Series ((LGTS,volume 3))

Abstract

How do we build an ontology? This chapter offers a review of some of the most important ontology development methodologies, tools and languages, and suggests an expert-based approach to the development of professional knowledge-based legal ontologies.

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Notes

  1. 1.

    Fernández-López (1999) discussed the question “Why and how can the IEEE Standard be applied to Ontology Development”, and argued that as the definition of software included in the IEEE Standard Glossary of Software Engineering Terminology (IEEE 610.12-1990) was “computer programs, procedures, and possibly associated documentation and data pertaining to the operation of a computer system”, concluded that as “ontologies are part (sometimes only potentially) of software products”, (…) “ontologies should be developed according to the standards proposed for software generally, which should be adapted to the special characteristics of ontologies”.

  2. 2.

    See: Schreiber et al. (1999) and http://www.commonkads.uva.nl/frameset-commonkads.html, retrieved August 18, 2010.

  3. 3.

    A detailed methodology to build legal ontologies based on METHONTOLOGY has been presented in Corcho et al. (2005).

  4. 4.

    “It is useful to write down a list of all terms we would like either to make statements about or to explain to a user. What are the terms we would like to talk about? What properties do those terms have? What would we like to say about terms?” (Noy and McGuinness2001).

  5. 5.

    Visit http://protege.stanford.edu/publications/ontology_development/ontology101.html, retrieved August 18, 2010, for more information.

  6. 6.

    For more information visit the Wiki Termontography at http://c2.com/cgi/wiki?WikiTermontography and the CVC webpage at http://taalkunde.ehb.be/cvc, and for more references on the method consult Temmerman and Kerremans (2003) and Kerremans et al. (2004).

  7. 7.

    The Cicero tool, developed for the NeOn Toolkit builds upon the DILIGENT methodology (Dellschaft et al.2008).

  8. 8.

    More information may be found at http://www-lipn.univ-paris13.fr/~szulman/TERMINAE.html, retrieved August 18, 2010.

  9. 9.

    Fidelity can be achieved with the verification of references to the sources used in the description of the terms modelled in the ontology, while Relevance and completeness involve the verification of the correct implementation of the initial requirements (e.g., competency questions).

  10. 10.

    More information on the NeOn European Project (Lifecycle Support for Networked Ontologies IST-2005-027595 6th Framework) may be found at http://www.neon-project.org/web-content. For a quick reference to ontology networks and ontology network life cycle models visit NeOn Methodology in a Nutshell at http://www.neon-project.org/web-content/index.php?option=com_content&view=article&id=153, retrieved August 18, 2010. For further reading, you may find the project deliverables at the NeOn Project website, in particular, Suárez-Figueroa et al. (2007, 2008a, b, 2009b, b)

  11. 11.

    “METHONTOLOGY does not consider the reuse and reengineering of non ontological resources, neither the reuse of ontology design patterns. Taking into account the important dimensions considered in the NeOn project, we can say that METHONTOLOGY does not mention anything about collaboration and context. Although some mention about the dynamic dimension is made, no detailed guidelines about how to manage different versions are given” (Suárez-Figueroa et al. 2008a).

  12. 12.

    The OntoClean ontology (OWL DL and OWL Full versions) may be found at: http://www.ontoclean.org. The Protégé ontology editor offers the possibility of implementing the OntoClean ontology towards evaluation. Moreover, AEON is proposed as a tool which automatically tags concepts with appropriate OntoClean meta-properties (Völker et al. 2005) (http://ontoware.org/projects/aeon, retrieved August 18, 2010).

  13. 13.

    Involves five activities: (1) organizing and scoping (purpose); (2) data collection; (3) data analysis; (4) initial ontology development, and (5) ontology refinement and validation. IDEF5 includes ontology languages. For more information regarding IDEF methods and commercial tools, visit: http://www.idef.com

  14. 14.

    In general, they all offer a iterative life-cycle model. CommonKADS “follows a spiral approach that enables structured learning” (Schreiber et al. 1999). METHONTOLOGY is based in the development of evolving prototypes (Fernández-López et al. 1997).

  15. 15.

    For particular information on some of these languages see, for example, Genesereth and Fikes (1992) and Gruber (1992).

  16. 16.

    W3C recommendation (16 August 2006, edited in place 29 September 2006): http://www.w3.org/TR/xml11, retrieved August 18, 2010.

  17. 17.

    W3C recommendation (10 February 2004): http://www.w3.org/TR/rdf-primer, retrieved August 18, 2010.

  18. 18.

    Triples can be written using XML tags. Visit http://www.w3.org/standards/techs/rdf\#w3c_all for more information on RDF.

  19. 19.

    For the RDF Vocabulary Description Language 1.0: RDF Schema, visit: http://www.w3.org/TR/rdf-schema/, retrieved August 18, 2010.

  20. 20.

    The relationship between RDF, OWL and SKOS is complex, read more details in the SKOS Simple Knowledge Organization System, Reference W3C Recommendation 18 August 2009 http://www.w3.org/TR/skos-reference, the SKOS Primer, W3C Working Group Note 18 August 2009 at http://www.w3.org/TR/skos-primerSKOS, retrieved August 18, 2010. More information may be found at the W3C SKOS webpage: http://www.w3.org/2004/02/skos, retrieved August 18, 2010.

  21. 21.

    DAML (DARPA Agent Markup Language, see http://www.daml.org) and OIL (ontology inference layer, see http://www.ontoknowledge.org/oil).

  22. 22.

    http://www.unicode.org

  23. 23.

    For details on XML technology visit http://www.w3.org/standards/xml/

  24. 24.

    Triples can be written using XML tags. Visit http://www.w3.org/standards/techs/rdf\#w3c_all for more information on RDF.

  25. 25.

    See Chap. 3 and visit http://www.w3.org/standards/techs/owl\#w3c_all, retrieved August 18, 2010, for more information.

  26. 26.

    For a succinct and description of the OWL language, including OWL 2 profiles, see Hoekstra (2009b).

  27. 27.

    All OWL 1 ontologies remain valid OWL 2 ontologies. For further details consult Hitzler et al. (2009) and http://www.w3.org/TR/2009/REC-owl2-overview-20091027/, retrieved August 18, 2010. For more details on OWL profiles read Motik et al. (2009) and Golbreich et al. (2009).

  28. 28.

    See, for example, the discussions regarding OWL-S. An overview may be found in Antoniou and van Harmelen (2008). See also: http://www.daml.org/services/owl-s, retrieved August 18, 2010.

  29. 29.

    Also, visit the World Wide Web Consortium (W3C) website for further developments on language specifications (http://www.w3.org).

  30. 30.

    “Developers of expert systems have spoken so much of the knowledge-acquisition ‘bottleneck’ that the expression has become a chiché. Nevertheless, knowledge acquisition remains the major difficulty in the creation of most practical knowledge bases” (Musen1993).

  31. 31.

    See, for example, Steels (1990), Musen (1993), Hoffman et al. (1995), Marcus (1999), Schreiber et al. (1999), Burge (1998) and Milton (2007).

  32. 32.

    “Although the aims of knowledge acquisition and ontology learning (from text) are certainly overlapping – in essence the acquisition of explicit knowledge implicitly contained in (textual) data – there are, however, also a number of novel and innovative aspects to ontology learning that sets it apart from much of the previous work in knowledge acquisition” (Buitelaar et al.2005b).

  33. 33.

    More information & download: http://www.jarrar.info/Dogmamodeler, retrieved August 18, 2010.

  34. 34.

    More information consult Debruyne et al. (2009) and De Leenheer and Debruyne (2010) and visit: http://starlab.vub.ac.be/website/dogmastudio, retrieved August 18, 2010.

  35. 35.

    DOGMA pipeline (see Fig. 3.15) from http://starlab.vub.ac.be/website/node/360, retrieved August 18, 2010.

  36. 36.

    Visit http://prologpluscg.sourceforge.net/index.html, retrieved August 18, 2010, for more information.

  37. 37.

    See also (Sugiura et al. 2004). More information and download from http://doddle-owl.sourceforge.net, retrieved August 18, 2010.

  38. 38.

    Jena: http://jena.sourceforge.net (For more information on Jena 2 inference support, visit http://jena.sourceforge.net/inference, retrieved August 18, 2010.

  39. 39.

    http://mr3.sourceforge.net, retrieved August 18, 2010.

  40. 40.

    More information is available in Kozaki et al. (2005) and Kumazawa et al. (2009). Hozo may be downloaded from http://www.ei.sanken.osaka-u.ac.jp/hozo, retrieved August 18, 2010. A discussion on the representation and formalization of roles in Hozo may be found in Kozaki et al. (2008).

  41. 41.

    KAON2 and tools may be downloaded from: http://kaon2.semanticweb.org and http://owltools.ontoware.org

  42. 42.

    “KAON is an open-source ontology management infrastructure targeted for business applications. It includes a comprehensive tool suite allowing easy ontology creation and management and provides a framework for building ontology-based applications”. The KAON IO modeler was developed by FZY and AIFB and is current release its 1.2.7 (April 2004). It is distributed under GNU Lesser General Public License and may be downloaded from http://sourceforge.net/projects/kaon, retrieved November 10, 2008.

  43. 43.

    OntoBroker: http://www.ontoprise.de/en/home/products/ontobroker.

  44. 44.

    NeOn IST-2005-027595, http://www.neon-project.org. More information and downloads may be found at http://neon-toolkit.org, retrieved August 18, 2010.

  45. 45.

    All previous versions plug-ins might not be available for the latest NeOn Toolkit version. The NeOn plug-ins may be found at http://neon-toolkit.org/wiki/Neon_Plugins

  46. 46.

    For a list of supported OWL2 features see the available documentation http://neon-toolkit.org/wiki/Documentation_and_Support

  47. 47.

    Information and downloads may be found at http://ksl.stanford.edu/software/ontolingua and http://www-ksl.stanford.edu/software/chimaera/, respectively.

  48. 48.

    More information and download from: http://protege.stanford.edu

  49. 49.

    Collaborative Protégé: http://protegewiki.stanford.edu/wiki/Collaborative_Protege, retrieved August 18, 2010.

  50. 50.

    WebProtégé: http://protegewiki.stanford.edu/wiki/WebProtege, retrieved August 18, 2010.

  51. 51.

    For more information consult (Vega2003) and visit http://www.oeg-upm.net

  52. 52.

    More information is available at TopQuadrant: http://www.topquadrant.com

  53. 53.

    A free trial version of this product is available at http://www.altova.com/semanticworks.html, retrieved August 18, 2010.

  54. 54.

    More information regardingOntoStudio may be found at Weiten (2009) and http://www.ontoprise.de/en/home/products/ontostudio/, retrieved August 18, 2010.

  55. 55.

    The HCONE2 tool integrates support for the collaborative engineering of ontologies, HCOME-3O (Kotis2010). More information on HCONE2 may be found at http://icsd-ai.aegean.gr/hcone/index.php, retrieved August 18, 2010.

  56. 56.

    DaFOE: http://dafoe4app.fr

  57. 57.

    SWOOP: http://code.google.com/p/swoop, retrieved August 18, 2010.

  58. 58.

    Further ontology editors such as OILed and OntoEdit are now no longer supported or maintained in their previous websites. OILed: http://oiled.man.ac.uk. OntoEdit: http://ontoserver.aifb.uni-karlsruhe.de/ontoedit

  59. 59.

    Denny (2004) offers a comparative table including 94 ontology editors, updated during 2004.

  60. 60.

    Maedche and Staab (2001) distinguished several approaches to ontology learning according to their input: free text, dictionary, knowledge base, semistructured schemata, and relational schemata.

  61. 61.

    Wordnet: http://wordnet.princeton.edu

  62. 62.

    “A simple technique for extracting relevant lexical entries that may indicate concepts is counting frequencies of terms in a given set of (linguistically preprocessed) documents, the corpus D. In general this approach is based on the assumption that a frequent term in a set of domain-specific texts indicates occurrence of a relevant concept” (Maedche and Staab2004).

  63. 63.

    For example, Buitelaar et al. (2005b) states that “concept induction or formation should provide: an intensional definition of the concept, a set of concept instances (…), and a set of linguistic realisations”. Aussenac-Gilles et al. (2000a) proposes the following method to get from text to concepts. “Terms and lexical relations are syntagms existing in the corpus and regarded as important in the domain. Lexical clustering puts together syntagms which occur in some similar contexts. The syntagms may be interpreted in a local context (sentence or paragraph) then in a global one (text or whole corpus). If they are considered as terms, they give rise to concepts and semantic relations that they label”.

  64. 64.

    DOODLE (Domain Ontology rapiD DeveLopment Environment) includes a module which analyses and extracts terms from an input English or Japanese textual corpus and reuses WordNet or other OWL ontologies to construct taxonomic and other relationships.

  65. 65.

    Alceste contains dictionaries for French, English, Spanish, Portuguese, Italian and German. And may be purchased from http://www.image-zafar.com/index_alceste.htm, retrieved August 18, 2010, (although a free, registration required, student version is available online).

  66. 66.

    This system works with most languages. AntConc is freely available and may be downloaded from http://www.antlab.sci.waseda.ac.jp/software.html, retrieved August 18, 2010.

  67. 67.

    It supports several languages and it may be freely downloaded from http://gate.ac.uk

  68. 68.

    May be downloaded from http://ontogen.ijs.si, retrieved August 18, 2010.

  69. 69.

    Other tools such as GlossExtractor, are also available. Visit: http://lcl2.uniroma1.it/tools.jsp, retrieved August 18, 2010.

  70. 70.

    OntoLT has been developed at DFKI GmbH (Germany). Version 2.0 works with Protégé 3.x and it may be downloaded from http://olp.dfki.de/OntoLT/OntoLT.htm, retrieved August 18, 2010.

  71. 71.

    http://cran.r-project.org, retrieved August 18, 2010.

  72. 72.

    Logiciel Terminae, developed at CNRS-LIPN and CNRS-IRIT, (version 12-4-2010) may be downloaded from http://www-lipn.univ-paris13.fr/~szulman/TERMINAE.html, retrieved August 18, 2010.

  73. 73.

    Developed at the Central Laboratory of Agriculture Expert Systems (Egypt) and Faculty of Computers and Information, Cairo University (Egypt).

  74. 74.

    See Lenci et al. (2009) and Spinosa et al. (2009).

  75. 75.

    Developed at the Institute of Applied Informatics and Formal Description Methods (AIFB, Universitaet Karlsruhe, Germany) is available from: http://code.google.com/p/text2onto, retrieved August 18, 2010.

  76. 76.

    NeOn Toolkit Text2Onto plugin is available from: http://www.neon-toolkit.org/wiki/1.x/Text2Onto, retrieved August 18, 2010.

  77. 77.

    Developed by Will Lowe at Harvard as part of the Identity Project at Harvard’s Center for International Affairs, it may be downloaded from http://www.yoshikoder.org

  78. 78.

    Lists of ontology and semantic web related tools may be found at http://semanticweb.org/wiki/Tools, retrieved August 18, 2010

  79. 79.

    http://pellet.owldl.com/ontology-browser, retrieved August 18, 2010.

  80. 80.

    ACE View is a Protégé (version 4) plug-in: http://attempto.ifi.uzh.ch/aceview, retrieved August 18, 2010.

  81. 81.

    Watson: http://kmi-web05.open.ac.uk/WatsonWUI/, retrieved August 18, 2010.

  82. 82.

    EVOLVA: http://www.neon-toolkit.org/wiki/Evolva, retrieved August 18, 2010.

  83. 83.

    A complete list of plug-ins for Protégé may be found at: http://protegewiki.stanford.edu/wiki/Protege_Plugin_Library, retrieved August 18, 2010. The list of plug-ins for the NeOn Toolkit may be found at http://www.neon-toolkit.org/wiki/Neon_Plugins, retrieved August 18, 2010.

  84. 84.

    A similar comment may be found in Noy and McGuinness (2001).

  85. 85.

    Rational Unified Process (RUP) is divided within six core engineering workflows: (1) business modelling workflow, (2) requirements workflow, (3) analysis and design workflow, (4) implementation workflow, (5) test workflow, and (6) deployment workflow Rational (2001).

  86. 86.

    “(…) CommonKADS has been influenced by other methodologies, including structured systems analysis and design, object orientation, organization theory, process reengineering, and quality management” (Schreiber et al. 1999). For an extensive description of software and knowledge engineering development and life-cycle processes see Suárez-Figueroa et al. (2007, 2008b).

  87. 87.

    ISO: http://www.iso.org/iso/home.htm

  88. 88.

    IEEE was originally an acronym for Institute of Electrical and Electronics Engineers, Inc. Visit IEEE at http://www.ieee.org and http://standards.ieee.org

  89. 89.

    ISO/IEC-9126 product quality metrics (internal and external) Standard (2001, 2003a, b, 2004c), IEEE-1074:2006 development of software project life-cycle process (IEEE2006), ISO/IEC-25000 series for the establishment of Software product Quality Requirements and Evaluation (SQuaRE) (Standard2005, 2007a, b), IEEE-830-1998 recommended practice for software requirements specifications, ISO/IEC-18019:2004 guidelines for the design and preparation of user documentation for application software (Standard2004b), IEEE-1012-2004 software verification and validation (IEEE2004), ISO/IEC-15288:2008 system life cycle processes (Standard2008b), ISO/IEC-12207:2008 (Standard2008a), ISO/IEC-15504 series for process assessment for information technologies (Standard2004a), ISO/IEC-14598 series for software product evaluation (Standard1999c), IEEE-1061-1998 quality metrics methodology (IEEE1998), ISO/IEC-14756-1999 measurement and rating of performance of computer-based software systems (Standard1999b), ISO/IEC-14764:2006 software maintenance (Standard2006b), and ISO/IEC-15289:2006 for the management of documentation (Standard2006c), within others.

  90. 90.

    Human and user-centred design for life cycle of interactive computer-based systems (Standard1999a), usability methods (Standard2002), and particular standards for the production of documentation, and the evaluation of quality in use (Standard1998, 2004b, c, 2006a).

  91. 91.

    Visit the Usability Professionals’ Association website: http://www.usabilityprofessionals.org

  92. 92.

    The TRUMP, Trial Application Usability Maturity Project, ESPIRIT Project (IST-1999-28015) was also partly funded by the European Commission. The UsabilityNet Project was funded under the 5th Framework Programme (IST-1999-29067), http://www.usabilitynet.org. Finally, the VNET5 Network was funded by the European Commission (IST-2000-25465) from January 2001–2003 (http://www.vnet5.org).

  93. 93.

    For example, relevant research has focused on the role of ethnography in systems design. See Sommerville et al. (1993), Hughes et al. (1994), Hughes et al. (1995), Blythin et al. (1997) and Sommerville (2004).

  94. 94.

    This table and other method information is available from: http://www.usabilitynet.org/tools/methods.htm

  95. 95.

    Some authors refer to this step also as ontology evaluation (Gómez-Pérez et al. 2003; Hartmann et al.2005; Brank et al.2005).

  96. 96.

    For example, the ontology requirements specification documents provided by On-To-Knowledge and NeOn.

  97. 97.

    The use of collaborative ontology modelling tools or methodologies could offer support towards sharedness in particular ontology development scenarios.

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Casellas, N. (2011). Methodologies, Tools and Languages for Ontology Design. In: Legal Ontology Engineering. Law, Governance and Technology Series, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1497-7_3

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