Supervised by: Ministry of Culture of PRC

Sponsored by:National Library of China
  Library Society of China

ISSN 1001-8867    CN 11-2746/G2

Safe Open Science for Restricted Data

Abstract

Open science is prompting wide efforts to make data from research available for broader use. However, sharing data is complicated by important protections on the data (e.g., protections of privacy and intellectual property). The spectrum of options existing between data needing to be fully open access and data that simply cannot be shared at all is quite limited. This paper puts forth a generalized remote secure enclave as a socio-technical framework consisting of policies, human processes, and technologies that work hand in hand to enable controlled access and use of restricted data. Based on experience in implementing the enclave for computational, analytical access to a massive collection of in-copyright texts, we discuss the synergies and trade-offs that exist between software components and policy and process components in striking the right balance between safety for the data, ease of use, and efficiency.

Keywords: open science;computational analysis;HathiTrust;capsule framework;restricted data;security;safe open science

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