Social Genome: Putting Big Data to Work for Population Informatics Academic Article

abstract

• Data-intensive research using distributed, federated, person-level datasets in near real time has the potential to transform social, behavioral, economic, and health sciences - but issues around privacy, confidentiality, access, and data integration have slowed progress in this area. When technology is properly used to manage both privacy concerns and uncertainty, big data will help move the growing field of population informatics forward. 1970-2012 IEEE.

authors

• Kum, Hye Chung

published proceedings

• COMPUTER

altmetric score

• 4.85

author list (cited authors)

• Kum, H., Krishnamurthy, A., Machanavajjhala, A., & Ahalt, S. C.

citation count

• 30

complete list of authors

• Kum, Hye-Chung||Krishnamurthy, Ashok||Machanavajjhala, Ashwin||Ahalt, Stanley C

publication date

• January 2014

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Computer  Journal

keywords

• Bioinformatics
• Data Handling
• Data Privacy
• Genomics
• Informatics
• Information Management
• Knowledge Base Platform
• Population Informatics
• Privacy-preserving Record Linkage
• Secure Data Access
• Social Genome
• Sociology
• Statistics

Digital Object Identifier (DOI)

• 10.1109/MC.2013.405

start page

• 56

end page

• 63

volume

• 47

issue

• 1

URL

• http://dx.doi.org/10.1109/mc.2013.405