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Data Sharing in Social Science Repositories: Facilitating Reproducible Computational Research

Stodden, Victoria C.

From new types of data to new computational methodologies, computation is engendering a revolution in social science research and with this comes the issue of facilitating data and code sharing to encourage collaboration and reproducibility in scientific publishing. A repository designed for this purpose at Harvard University, the Dataverse Network, permits authors to upload data and code with their own terms of use. This paper examines these terms of use for 30,090 uploads to discover barrier issues to sharing in the social sciences and compares them to those found in a survey of NIPS registrants. We find that the additionally specified terms of use in The Dataverse Network primarily address issues of maintaining subject confidentiality, preventing further sharing, making specific citation a condition of use, restricting access by commercial or profit-making entities, and time embargoes, which differs to those elucidated among NIPS participants. Using these findings we suggest a sharing framework for social science data to expand engagement of the larger social science community and encourage verification of research findings.

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October 3, 2011

Notes

Presented at the Neural Information Processing Systems workshop, "Computational Social Science and the Wisdom of Crowds," Whistler, B.C., December 10-11, 2010.

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