Scientific communication must be re-engineered. Complex analyses from biomedical research are outpacing the means to convey them effectively. Imprisoning insights gleaned from these data to a few two-dimensional representations is wholly inadequate for transmitting the complexity of “big science” to our peers and the public. Numerous editorials and papers, as well as the cancer genomics scandal at Duke University highlight the need for infrastructure that supports reproducible and transparent science. When only 11% of landmark cancer studies can be independently confirmed, it is clear that serving our patients requires a new standard of openness and reproducibility. If scientific progress depends on our being able to effectively communicate our science so that the community can build upon it, evidence shows that we need to improve.
As a not-for-profit research organization, Sage Bionetworks is charged with exploring open models in the practice of biomedical science and enhancing the value of medical research to the community. The foundation for this exploration is Synapse, a cloud-based platform which co-locates data, code, and computing resources for analyzing genome-scale data and seamlessly integrates these services. While typical scientific publications are a minor elaboration on a 15th century technology, we propose that ‘publication’ of data-intensive science should not just be a representation of science, but the science itself.
We will present clearScience, a pilot project in building infrastructure for effective scientific communication. By leveraging Synapse services, we demonstrate how scientists can easily transition from exploring data—executing science—and providing the scientific community all the resources to recreate analyses. By capturing the complete lifecycle of a project, reproducibility becomes a byproduct rather than a burden of publication. Further, we provide for “forking an analysis”, allowing anyone to explore and elaborate on ‘published’ work. If the goal of biomedical research is to deliver results that will ultimately alleviate suffering and minimize harm to patients, being able to transparently share, reproduce, and build off of one another’s work is critical to scientific progress. clearScience represents one compelling model for facilitating this progress.
Brian is a Senior Scientist at Sage Bionetworks, a not-for-profit organization dedicated to exploring open source models in the advancement of biomedical research in Seattle, Washington. Brian received a BS at the University of Minnesota in Statistics and worked as a Biostatistician at the Mayo Clinic in Rochester, MN for 7 years. Brian’s extensive experience in working with clinical and genomic data, combined with his passion for exploring innovative ways to make science more open and transparent guided him to Sage Bionetworks.
Brian’s current projects involve implementing strategies and technologies for making complex genomic data more usable and accessible to the community, and re-envisioning how scientists communicate complex genomic science to one another and to the public at large though clearScience.
Erich S. Huang is Director of Cancer Research at Sage Bionetworks in Seattle, Washington. He received his PhD in Genetics and his MD from Duke University. Erich has long been interested in how genome-scale science lies at the intersection of discovery science and informatics, and how open source research models might be promoted to improve the quality and usability of biomedical research.
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