Safe Open Science for Restricted Data

被引:1
|
作者
Plale B.A. [1 ]
Dickson E. [2 ]
Kouper I. [3 ]
Harshani Liyanage S. [4 ]
Ma Y. [4 ]
McDonald R.H. [5 ]
Walsh J.A. [6 ]
Withana S. [1 ]
机构
[1] Department of Intelligent Systems Engineering, School of Informatics, Computing, and Engineering, Indiana University, Bloomington
[2] HathiTrust, University of Michigan, Ann Arbor, MI
[3] Department of Informatics, School of Informatics, Computing, and Engineering, Indiana University, Bloomington
[4] HathiTrust Research Center, Indiana University, Bloomington
[5] University Libraries, University of Colorado Boulder, Boulder, CO
[6] Department of Information and Library Science, School of Informatics, Computing, and Engineering, Indiana University, Bloomington
来源
Data and Information Management | 2019年 / 3卷 / 01期
基金
美国安德鲁·梅隆基金会;
关键词
capsule framework; computational analysis; HathiTrust; open science; restricted data; safe open science; security;
D O I
10.2478/dim-2019-0005
中图分类号
学科分类号
摘要
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. © 2019 © 2019 Beth A. Plale et al., published by Sciendo
引用
收藏
页码:50 / 60
页数:10
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