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