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PUBLIC RELEASE DATE:
19-Feb-2011

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Contact: Beth Kwon
beth.kwon@columbia.edu
212-854-6581
Columbia University

AAAS Symposium: New research facilitates scientific knowledge transfer

New tools provide urgently needed solutions to resolve the reproducibility crisis in computational science

NEW YORK, February 4, 2011 -- A defining feature of a scientific discovery is replication by others. In today's age of computational science, this means higher standards of communication of discoveries -- making available the data that generated the results along with the published research paper. Doing this makes the technology behind the finding widely accessible, facilitating re-use and verification of results.

Tools and approaches to facilitate such knowledge transfer will be discussed at a symposium titled The Digitization of Science: Reproducibility and Interdisciplinary Knowledge Transfer at the American Association for the Advancement of Science Annual Meeting in Washington, DC, on Saturday, February 19, 1:30 p.m. to 4:30 p.m., in 159AB Washington Convention Center.

Victoria Stodden, Columbia University, symposium organizer
vcs2115@columbia.edu, 212-851-2130

Keith Baggerly, M.D. Anderson Cancer Research Center
kabagg@mdanderson.org, 713-563-4290

David Donoho, Stanford University
donoho@stanford.edu, 650-723-3350

Matan Gavish, Stanford University
gavish@stanford.edu, 650-723-2620

Robert Gentleman, University of Washington
rgentlem@gmail.com, 206-667-7700

Mark Liberman, University of Pennsylvania
myl@cis.upenn.edu, 215-898-6046

Michael Reich, Broad Institute of Harvard and MIT
michaelr@broadinstitute.org, 617-714-7000

Fernando Perez, University of California at Berkeley
Fernando.perez@berkeley.edu, 510-643-4010

Included among the range of new tools for presentation at the symposium are Donoho and Gavish's Universal Identifier for Computational Results which creates a registry for computational results that provides replication and citation information; Stodden's Reproducible Research Standard, a suite of open licenses to bring the intellectual property framework faced by computational scientists in line with longstanding scientific norms; Baggerly's case study of the widely discussed 2010 terminated clinical trials at Duke occurring in part because of efforts by his lab to reproduce the associated studies; and Liberman's technical communication methodologies learned from the DARPA Speech and Language Program.

The AAAS symposium highlights how such knowledge transfer can detect flawed science and the importance of reproducibility for error control. Open code and data permits computational science to achieve standards for reproducibility that characterize the scientific endeavor, and maximize the wide availability of scientific knowledge.

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