Quantifying patent commercialisation to support engineering design

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This project will investigate if crowdsourcing can be used to aggregate the content of disparate, open-data sources across the internet to determine which patents underpin commercial products, and organise and present these according to technical criteria in a visual "gallery" form appropriate for engineering design.Patents are frequently used to quantify levels of innovation associated with specific regions or companies. However despite the development of sophisticated data mining tools to support the analysis of over 50 million online patent records, little is known about which patents are actually "commercialized" and how they are embodied in commercial products. Because of this "patent informatics" has been inherently limited to the study of the records, rather than the use, of Intellectual Property (IP). This information gap inevitably reduces the accuracy of academic and commercial analysis that use patent data for applications such as innovation research, R&D fore-sighting, and IP portfolio valuations. Furthermore, the presentation of existing data maps is not in a form that is useful for engineering designers when conceptualising and embodying products: it is predominantly text-based (and often deliberately obfuscated) when more visual presentation with exemplars and appropriate technical taxonomic terms would greatly enhance utility when undertaking engineering design development.Crowdsourcing utilises large networks of open people to compete discrete tasks. Virtual tools are used to co-ordinate the distribution, payment and co-ordination of results, resulting in a labour market that is open 24/7 and a diverse workforce available to perform tasks quickly and cheaply. The distributed network of human workers provide on-line, "black-box", reasoning capabilities that could far exceed the capabilities of current AI technologies (i.e. genetic algorithms, neural-nets, case-based reasoning) in terms of flexibility and scope. This project proposes that crowdsourcing can be utilised to access open data sources such as user manuals, product labelling, court proceedings and company web pages to understand which patents are actively used in current products and how they have been embodied. With a more accurate representation of innovation commercialisation, technical metadata (labelling), and utilisation, we envisage patent searches not as a stage-gate check but as a revitalised source of design inspiration. Indeed, if crowdsourcing proves a cheap, scalable way of collating this information and applying appropriate taxonomic and visual engineering information, it could fundamentally alter the early phases of engineering design. To this end, the project will result in a visualization tool that can be used to both guide and inspire design conceptualisation and embodiment.