NIF Webinar: Feb 19th 11 am PDT: Sage Bionetworks discusses ClearScience

Please join us to discuss the future of scientific communication as seen by SAGE Bionetworks.

Title: clearScience: Dragging Scientific Communication into the Information Age
Presenter: Erich Huang & Brian Bot (Sage Bionetworks)
Date: February 19th, 2013; 11 am PDT
Where: http://connect.neuinfo.org/webinar

Abstract: 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.