Privacy preserving data visualizations

被引：0
作者：
Demetris Avraam
Rebecca Wilson
Oliver Butters
Thomas Burton
Christos Nicolaides
Elinor Jones
Andy Boyd
Paul Burton
机构：
[1] Newcastle University,Population Health Sciences Institute
[2] University of Cyprus,Department of Business and Public Administration
[3] University of Liverpool,Department of Public Health, Policy and Systems, Institute of Population Health
[4] University of Oxford,Department of Computer Science
[5] University of Cyprus,Nireas Research Center
[6] Massachusetts Institute of Technology,Sloan School of Management
[7] University College London,Department of Statistical Science
[8] University of Bristol,Population Health Sciences, Bristol Medical School
来源：
EPJ Data Science | / 10卷
关键词：
Sensitive data; Data visualizations; Disclosure control; Privacy protection; Anonymization;
D O I：
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中图分类号：
学科分类号：
摘要：
Data visualizations are a valuable tool used during both statistical analysis and the interpretation of results as they graphically reveal useful information about the structure, properties and relationships between variables, which may otherwise be concealed in tabulated data. In disciplines like medicine and the social sciences, where collected data include sensitive information about study participants, the sharing and publication of individual-level records is controlled by data protection laws and ethico-legal norms. Thus, as data visualizations – such as graphs and plots – may be linked to other released information and used to identify study participants and their personal attributes, their creation is often prohibited by the terms of data use. These restrictions are enforced to reduce the risk of breaching data subject confidentiality, however they limit analysts from displaying useful descriptive plots for their research features and findings.
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[1]  
Healy K(2014)Data visualization in sociology Annu Rev Sociol 40 105-128
[2]  
Moody J(2010)Visualizing biological data–now and in the future Nat Methods 7 2-4
[3]  
O’Donoghue SI(2018)Visualization of biomedical data Annu Rev Biomed Data Sci 1 275-304
[4]  
Gavin A-C(1998)The impacts of presentation visuals on persuasion Inf Manag 33 125-135
[5]  
Gehlenborg N(2015)Putting environmental infographics center stage: the role of visuals at the elaboration likelihood model’s critical point of persuasion Sci Commun 37 6-33
[6]  
Goodsell DS(2015)Seeing is believing: good graphic design principles for medical research Stat Med 34 3040-3059
[7]  
Hériché J-K(2018)Are ‘pseudonymised’ data always personal data? Implications of the GDPR for administrative data research in the UK Comput Law Secur Rev 34 222-233
[8]  
Nielsen CB(2015)Data safe havens in health research and healthcare Bioinformatics 31 3241-3248
[9]  
North C(2016)Data safe havens and trust: toward a common understanding of trusted research platforms for governing secure and ethical health research JMIR Med Inform 4 557-570
[10]  
Olson AJ(2002)K-anonymity: a model for protecting privacy Int J Uncertain Fuzziness Knowl-Based Syst 10 433-446
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