Name
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/MC.2013.405 | IEEE Computer |
Keywords | DocType | Volume |
near real time,data access,big data,data privacy,data confidentiality,health sciences,privacy-preserving record linkage,social genome,distributed datasets,population informatics,privacy concern,Big Data,person-level datasets,federated dataset,knowledge base platform,data integration,social sciences computing,secure data access,data-intensive research,health science | Journal | 47 |
Issue | ISSN | Citations |
1 | 0018-9162 | 9 |
PageRank | References | Authors |
0.52 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hye-Chung Kum | 1 | 114 | 12.99 |
| Ashok Krishnamurthy | 2 | 455 | 56.47 |
| Ashwin Machanavajjhala | 3 | 2624 | 132.52 |
| Stanley Ahalt | 4 | 10 | 0.98 |