Discovering and assessing fields of expertise in nanomedicine: a patent co-citation network perspective

Discovering and assessing fields of expertise in emerging technologies from patent data is not straightforward. First, patent classification in an emerging technology being far from complete, the definitions of the various applications of its inventions are embedded within communities of practice. Because patents must contain full record of prior art, co-citation networks can, in theory, be used to identify and delineate the inventive effort of these communities of practice. However, the use patent citations for the purpose of measuring technological relatedness is not obvious because they can be added by examiners. Second, the assessment of the development stage of emerging industries has been mostly done through simple patent counts. Because patents are not all valuable, a better way of evaluating an industry's stage of development would be to use multiple patent quality metrics as well as economic activity agglomeration indicators. The purpose of this article is to validate the use of (1) patent citations as indicators of technological relatedness, and (2) multiple indicators for assessing an industry's development stage. Greedy modularity optimization of the ‘Canadian-made' nanotechnology patent co-citation network shows that patent citations can effectively be used as indicators of technological relatedness. Furthermore, the use of multiple patent quality and economic agglomeration indicators offers better assessment and forecasting potential than simple patent counts.

Mots clés

Knowledge discovery, Nanomedicine, Self-organization, Trend analysis, Citation network analysis, S-curve