The mission of the social sciences is to understand and ameliorate society’s greatest challenges. The data held by private companies, collected for different purposes, hold vast potential to further this mission. Yet, because of consumer privacy, trade secrets, proprietary content, and political sensitivities, these datasets are often inaccessible to scholars. We propose a novel organizational model to address these problems. We also report on the first partnership under this model, to study the incendiary issues surrounding the impact of social media on elections and democracy: Facebook provides (privacy-preserving) data access; eight ideologically and substantively diverse charitable foundations provide funding; an organization of academics we created, Social Science One (see SocialScience.One), leads the project; and the Institute for Quantitative Social Science at Harvard and the Social Science Research Council provide logistical help.
Informatics and Data Sharing
Replication Standards New standards, protocols, and software for citing, sharing, analyzing, archiving, preserving, distributing, cataloging, translating, disseminating, naming, verifying, and replicating scholarly research data and analyses. Also includes proposals to improve the norms of data sharing and replication in science.
A New Model for Industry-Academic Partnerships.” PS: Political Science and Politics. Publisher's VersionAbstract
. 2019. “
"The replication standard holds that sufficient information exists with which to understand, evaluate, and build upon a prior work if a third party can replicate the results without any additional information from the author." This, and the data sharing to support it, was proposed for political science, along with policy suggestions in . 1995. “Replication, Replication.” PS: Political Science and Politics, 28, Pp. 444-452.Abstract
Preface: Big Data is Not About the Data!” In Computational Social Science: Discovery and Prediction, . Cambridge: Cambridge University Press.Abstract
. 2016. “
Comments from nineteen authors and a response to the above: . 1995. “A Revised Proposal, Proposal.” PS: Political Science and Politics, XXVIII, Pp. 494–499.
Publication, Publication.” PS: Political Science and Politics, 39, Pp. 119–125. Continuing updates to this paperAbstract
. 2006. “The Dataverse Network Project
The Dataverse Network Project: a major ongoing project to write web applications, standards, protocols, and software for automating the process of citing, archiving, preserving, distributing, cataloging, translating, disseminating, naming, verifying, and replicating data and associated analyses (Website: TheData.Org). See also:
An Introduction to the Dataverse Network as an Infrastructure for Data Sharing.” Sociological Methods and Research, 36, Pp. 173–199.Abstract
. 2007. “
Automating Open Science for Big Data.” ANNALS of the American Academy of Political and Social Science, 659, 1, Pp. 260-273. Publisher's VersionAbstract
. 2015. “Hidden Section 1
A symposium on replication, edited by Nils Petter Gleditsch and Claire Metelits, with several articles including mine, . 2003. “The Future of Replication.” International Studies Perspectives, 4, Pp. 443–499.Abstract
The Virtual Data Center
The Virtual Data Center, the predecessor to the Dataverse Network. See:
An Introduction to the Virtual Data Center Project and Software.” Proceedings of The First ACM+IEEE Joint Conference on Digital Libraries, Pp. 203–204.
. 2001. “
A Digital Library for the Dissemination and Replication of Quantitative Social Science Research.” Social Science Computer Review, 19, Pp. 458–470.Abstract
. 2001. “See Also
Comment on 'Estimating the Reproducibility of Psychological Science'.” Science, 351, 6277, Pp. 1037a-1038a. Publisher's VersionAbstract
. 2016. “Related Papers on New Forms of Data
Ensuring the Data Rich Future of the Social Sciences.” Science, 331, 11 February, Pp. 719-721.Abstract
. 2011. “
The Changing Evidence Base of Social Science Research.” In The Future of Political Science: 100 Perspectives, . New York: Routledge Press.Abstract
. 2009. “
Preserving Quantitative Research-Elicited Data for Longitudinal Analysis. New Developments in Archiving Survey Data in the U.S.” Historical Social Research, 34, 3, Pp. 51-59.Abstract
. 2009. “
Computational Social Science.” Science, 323, Pp. 721-723.Abstract
. 2009. “