We believe computational science as practiced today suffers from a growing credibility gap – it is impossible to replicate most of the computational results presented at conferences or published in papers today. We argue that this crisis can be addressed by the open availability of the code and data that generated the results, in other words practicing reproducible computational science. In this paper we present a new computational infrastructure called RunMyCode.org that is designed to support published articles by providing a dissemination platform for the code and data that generated the their results. Published articles are given a companion webpage on the RunMyCode.org website from which a visitor can both download the associated code and data, and execute the code in the cloud directly through the RunMyCode.org website. This permits results to be verified through the companion webpage or on a user’s local system. RunMyCode.org also permits a user to upload their own data to the companion webpage to check the code by running it on novel datasets. Through the creation of “coder pages” for each contributor to RunMyCode.org, we seek to facilitate social network-like interaction. Descriptive information appears on each coder page, including demographic data and other companion pages to which they made contributions. In this paper we motivate the rationale and functionality of RunMyCode.org and outline a vision of its future.
Stodden, Victoria, Hurlin, Christophe and Perignon, Christophe, RunMyCode.Org: A Novel Dissemination and Collaboration Platform for Executing Published
Computational Results (September 15, 2012). Available at SSRN: http://ssrn.com/abstract=2147710 or http://dx.doi.org/10.2139/ssrn.2147710
Columbia University - Department of Statistics ( email )