An Empirical Study of Open Source Bioinformatics Software

The post-genomic era is characterized by a strong and growing need for bioinformatics software tools designed to analyze and organize structural and functional genomic information. Intellectual property protection and licensing practices are expected to have a profound impact on the creation, distribution and utilization of bioinformatics software tools. In the bioinformatics community, there are differing views on how to best promote the creation and distribution of bioinformatics software. In 2001, a group of bioinformatics scientists petitioned the National Institute of Health (NIH) and National Science Foundation (NSF) to require grantees to distribute software developed under grant support under open source licenses. However, a number of bioinformaticists have argued that funding agencies should not require that grant-funded software development projects be distributed under open source licenses. These researchers cites the lack of empirical evidence supporting the assertion that software tools distributed under open source model have a significantly higher probability of success. This policy debate highlights the need for empirical research on the effects of open source software on adoption and use of genomic analysis tools. In response to this need, recent research efforts have been focused on obtaining empirical evidence for the analysis of the open source software development model. However, the question of whether an open source licensing model fosters the use of genomic software tools and encourages innovation in the research community remains largely unanswered. To this end, we propose the following specific aims: 1. To develop a system for monitoring the success of bioinformatics software tools and conducting empirical research using peer-reviewed scientific publications; 2. To investigate the adoption of a genomic analysis software under a dual license approach, using publication citation and user survey data; 3. To analyze the effect of open source and commercial licenses on genomic analysis software innovation, as defined by software improvements and derivatives from the original software package; and 4. To formulate a public policy recommendation, based on the above research studies, for genomic analysis software licensing strategies.