Social Genome: Putting Big Data to Work for Population Informatics

Author

Hye-Chung Kum ; Krishnamurthy, Arvind ; Machanavajjhala, A. ; Ahalt, Stanley C.

Volume

47

Issue

1

fYear

2014

fDate

Jan. 2014

Firstpage

56

Lastpage

63

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.

Keywords

Big Data; data integration; data privacy; social sciences computing; Big Data; data access; data confidentiality; data integration; data privacy; data-intensive research; distributed datasets; federated dataset; health sciences; person-level datasets; population informatics; social genome; Big data; Bioinformatics; Data handling; Genomics; Informatics; Information management; Knowledge based systems; Privacy; Sociology; Statistics; data privacy; knowledge base platform; population informatics; privacy-preserving record linkage; secure data access; social genome;

fLanguage

English

Journal_Title

Computer

Publisher

ieee

ISSN

0018-9162

Type

jour

DOI

10.1109/MC.2013.405

Filename

6678338