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A transdisciplinary ontology of innovation governance

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Abstract

Intellectual property law tends to be viewed as the only (or most significant) mechanism for achieving policy goals relating to innovation assets. Yet more creative and effective solutions are often available. When analysed from a transdisciplinary perspective, relying on the cooperative efforts of researchers from fields other than law, innovation governance is characterized not simply as the product of legal rules, but as a function of the interaction of legal rules, practices and institutions. When policy-makers seek to identify conditions under which the creation, use and exchange of innovation assets flourishes, care should be taken to focus on this combination of factors. This article describes the development of an ontology—a computerized method of representing knowledge as concepts and relations between concepts—to convey such understanding. Policy makers (and researchers) are provided with an organized, accessible representation of innovation governance that enriches their understanding and improves their decision-making.

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Notes

  1. I used the term “ostensibly” here to indicate that a utilitarian rationale of intellectual property dominates in both doctrine and jurisprudence. Other theories of justification do exist. See Justin Hughes, “The Philosophy of Intellectual Property” (1988) 77 Geo. L.J. 287.

  2. See e.g. U.S. Const. art. I, § 8, cl. 8; Théberge v. Galerie d’Art du Petit Champlain, 2002 SCC 34, [2002] 2 S.C.R. 336 at para. 30.

  3. A Quicklaw search of North American legal journals revealed 394 copyright or patent-related articles published in 2006, in comparison to 58 in 1982.

  4. Gold et al. (2004, pp. 301–306).

  5. “Transdisciplinary” is used here to indicate that researchers have collaborated to produce a methodology and perspective that transcends their individual disciplines, such as common vocabulary. Thus transdisciplinary work is distinguished from interdisciplinary work, where researchers’ contributions to a collaborative project are based on discipline-specific methodologies and perspectives.

  6. A description of the IPMG’s methodology in its entirety is beyond the scope of this article. See ibid. at pp. 320–322; “Description of IPMG Research Approach”, online: Centre For Intellectual Property Policy http://www.cipp.mcgill.ca/data/publications/00000047.pdf

  7. The IPMG does not recommend any particular policy objective. Instead, research is directed towards helping policy-makers and researchers in designing effective and creative strategies for using intellectual property to achieve desired objectives.

  8. Sterman (2000, pp. 12–14, 107–133).

  9. See Gold et al., supra note 4 at p. 321.

  10. This example ignores for the moment the possibility of negative relationships between government use and increased public access to information. For example, if government use is made available on terms that fall below market value, even though they are commercially reasonable, this may act as a disincentive to engage in research and development and thus would eventually decrease access to innovation.

  11. See e.g. Bayh-Dole University and Small Business Patent Procedures Act of 1980, Pub. L. No. 96-517, 94 Stat. 3015 (codified as amended at 35 U.S.C. § 200–212 (1994)).

  12. Note that while the ontological representation of innovation governance is developed to implement the results of the dynamic simulation, the ontology can also be used as a standalone application. If the significance of a variable, such as government use, and the nature of its relationship to a desired policy outcome, such as increased access to technology, is uncontested (or validated through a method other than a dynamic simulation), then the ontology can be used independently of the analysis provided by a dynamic simulation. Policy-makers and researchers will still be able to benefit from the capacity provided by the ontology to understand and focus on innovation governance more broadly as a function of the interaction of legal rules, practices and institutions, and to use this understanding to identify alternative methods for achieving a particular objective in relation to the creation and exchange of innovation assets.

  13. See e.g. the discussion of various methods of ontology generation in Ding and Foo (2002). For a discussion of ontology generation using natural language processing in the legal domain, see Lame (2004).

  14. The author is applying for additional funding to continue development of the ontology through the use of automated processes of ontology generation.

  15. See e.g. Supekar (2005). Reference to how the ontology has been reviewed by users is characterized as subjective because the possibility exists that users may evaluate the ontology as serving its stated purpose, and yet be in error in making this assessment.

  16. See e.g. Asuncion Gomez-Perez (2001).

  17. See e.g. Gomez-Perez (2002).

  18. See e.g. Gangemi et al. (2005) and Burton-Jones et al. (2005).

  19. See e.g. Jones et al. (1998) and Fernandez (1999).

  20. See e.g. the discussion of various methods for building ontologies in B.C. Vickery (1997). For discussions of methodologies for building legal ontologies, see Van Kralingen et al. (1999) and Corcho et al. (2005, p. 142).

  21. See e.g. Guarino (1995).

  22. See e.g. Uschold and Grüninger (1996).

  23. See e.g. Gruber (1995, p. 907, 908).

  24. Jacob (2003).

  25. See, for example, Vickery (1997). See also Soergel (1999). Although note that the problem of communication exists in both directions. See Hjorland (2000, 2002).

  26. See e.g. Chi et al. (2006).

  27. For a brief overview citing a number of examples of legal ontologies, see Visser and Bench-Capon (1998). See also Valente (2005, p. 65). For individual approaches to legal ontologies, see e.g. Mommers (2004), Hage and Verheij (1999), Breuker et al. (1997).

  28. Valente and Breuker (1996).

  29. For a brief description of various ontology development languages and tools, see Su and Ilebrekke (2002).

  30. The W3C is an international standards organization for the World Wide Web.

  31. Berners-Lee et al. (2001).

  32. For information on the OWL web ontology language and the semantic web, see “Web Ontology Language (OWL)”, online: W3C http://www.w3.org/2004/OWL/

  33. This may appear to be a self-referential assessment of validity, that is to say, that the measure of whether the appropriate theoretical basis has been chosen is a measure of the degree to which the IPMG members consider their theoretical approach to innovation governance to be valid. Given that ontology design, however, is a constitutive process involving an explicit (and shared) specification of a conceptualization (T. Gruber, http://www.ksl.stanford.edu/kst/what-is-an-ontology.html), to the extent that the IPMG members agree that the theoretical account accurately represents and explains domain knowledge, the self-referential nature of the classification process at the pre-implementation stage is unavoidable.

  34. Agreement on Trade-Related Aspects of Intellectual Property Rights, 15 April 1994, 1869 U.N.T.S. 299, 33 I.L.M. 1197 (1994) [TRIPS].

  35. The representative sample is currently limited to North American publications. Further development of the ontology will address this limitation by drawing upon a wider variety of sources.

  36. Random sampling of the relevant databases was supplemented by tacit knowledge of the IPMG in selecting the works of authors acknowledged as influential in their fields of expertise. Random sampling was also limited to post-TRIPS commentary, given the radical nature of the changes introduced by this international agreement concerning universal minimum standards of protection (see TRIPS, supra note 34).

  37. Knowledge concerning the particular problem to which the solution is addressed is discarded as this knowledge does not contribute to representing the possible modalities through which changes can be made to patent law. This does not mean that the information is invalid (this is most certainly not the case), but merely that the information is not suited to the ontology’s purpose, as the authors of the various articles are not working within the same conceptual framework as the IPMG.

  38. See, for example, Foo, supra note 13, p. 125.

  39. Hjorland and Pederson (2005).

  40. See Van de Ven and Delbecq (1972).

  41. See, for example, Uddin and Janecek (2006). Note that the mutually independent categories may subsequently be organized in the form of a type–subtype hierarchy.

  42. The proposed methodology for specifying all of the relationships between presumptively positive and negative modalities in relation to each variable is once again that of the nominal group method, the benefit being that this method capitalizes on the transdisciplinary nature of the knowledge acquired by the IPMG. At the current stage of development, however, the ontology represents a proof of concept and thus the relationships have not been subject to the nominal group method.

  43. TRIPS, supra note 34.

  44. The manner in which a patented invention is sold, for example, may violate competition law.

  45. For example, after global outcry from NGOs, Monsanto announced that it would abandon its controversial plan to market “terminator” seeds (Lambrecht 1999); “Genetic Engineering: Monsanto to Abandon Terminator Seeds Plan” Europe Agri (8 October 1999) (QL).

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Acknowledgements

This research project benefited from funding provided by the Social Sciences and Humanities Research Council of Canada and the Canadian Institutes of Health Research. I would also like to thank the many students who have worked on this project over the past 3 years, including Andrew Brighten, LL.B.-B.C.L. 2009 (McGill).

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  1. Faculty of Law, McGill University, 3644 Peel Street, H3A 1W9, Montreal, QC, Canada

    Wendy Ann Adams

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Adams, W.A. A transdisciplinary ontology of innovation governance. Artif Intell Law 16, 147–174 (2008). https://doi.org/10.1007/s10506-007-9060-2

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