Open source bioinformatics : the intersection between formal intellectual property laws and user generated laws in the scientific research commons

This thesis examines the interplay between national copyright and patent laws, and informal user generated norms in the governance of open source bioinformatics projects. Bioinformatics describes an interdisciplinary merger between computer science, statistics and molecular biology for quantitative biology analysis. As for many computationally driven scientific fields, there is a strong initiative both by researchers inside and outside the field to encourage collaborative research through open source software and data licensing. However, a trend towards seeking exclusive copyright and patent protection for bioinformatics algorithms could foster exclusivity and discourage collaboration in bioinformatics. Whether this effect exists within bioinformatics research, and if so is best resolved through national copyright and patent reform or private ordering strategies (which are already present through open source licensing) is a matter of open debate. This thesis explores these issues using a mixed methods, grounded theory framework that compares open licensing of bioinformatics software across the US, the EU, Australia and New Zealand. This framework operates on three levels: firstly, with a doctrinal analysis of copyright and patent laws (as well as related sui generis rights for data compilations); secondly, with a quantitative analysis of patent applications in bioinformatics and forward citation rates for patent publication pairs to determine whether the grant of these patents has a negative effect on citation rates; and thirdly, through semi-structured interviewing of bioinformaticians who release open source software and also seek patent protection. Each of these layers of analysis reveals that national patent laws do not appear to have a significant effect on the formation and governance of open source bioinformatics communities, but law reform targeted at encouraging private ordering strategies through copyright licensing might have a positive effect. This thesis concludes by offering recommendations on assessing how private ordering strategies in open source bioinformatics can be improved to encourage collaborative research.