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Data Sharing and Access
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AI
DOI：10.1146/annurev-statistics-041715-033438.png)
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摘要
En 中文
Data sharing and access are venerable problems embedded in a rapidly changing milieu. Pressure points include the increasingly data-driven nature of science, the volume, complexity, and distributed nature of data, new concerns regarding privacy and confidentiality, and rising attention to reproducibility of research. In the context of research data, this review surveys extant technologies, articulates a number of identified and emerging issues, and outlines one path for the future. Recognizing that data availability is a public good, research data archives can provide economic and scientific value to both data generators and data consumers in a way that engenders trust. The overall framework is statistical-the use of data for inference.
Keyword:
DISCLOSURE LIMITATION
STATISTICAL-ANALYSIS
REGRESSION
MICRODATA
PRIVACY
UTILITY
SECURE
FRAMEWORK
SYSTEMS
MODEL
期刊
IF:
8.7
论文数:
211
被引数:
2.4K
机构
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