Certify reproducibility with confidential data
Christophe Pérignon,
Kamel Gadouche (),
Christophe Hurlin,
Roxane Silberman and
Eric Debonnel
Additional contact information
Christophe Pérignon: HEC Paris - Ecole des Hautes Etudes Commerciales
Kamel Gadouche: CASD - Centre d'Accès Sécurisé aux Données (Groupe des écoles nationales d’économie et statistique (GENES))
Roxane Silberman: CASD - Centre d'Accès Sécurisé aux Données (Groupe des écoles nationales d’économie et statistique (GENES))
Eric Debonnel: CASD - Centre d'Accès Sécurisé aux Données (Groupe des écoles nationales d’économie et statistique (GENES))
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Abstract:
Many government data, such as sensitive information on individuals' taxes, income, employment, or health, are available only to accredited users within a secure computing environment. Though they can be cumbersome to access, such microdata can allow researchers to pursue questions that could not be addressed with only public data (1). However, researchers using confidential data are inexorably challenged with regard to research reproducibility (2). Empirical results cannot be easily reproduced by peers and journal referees, as access to the underpinning data are restricted. We describe an approach that allows researchers who analyze confidential data to signal the reproducibility of their research. It relies on a certification process conducted by a specialized agency accredited by the confidential-data producers and which can guarantee that the code and the data used by a researcher indeed produce the results reported in a scientific paper.
Date: 2019-07-12
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Citations: View citations in EconPapers (8)
Published in Science, 2019, 365 (6449), pp.127-128. ⟨10.1126/science.aaw2825⟩
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03528358
DOI: 10.1126/science.aaw2825
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