Title |
Ethics and Epistemology in Big Data Research
|
---|---|
Published in |
Journal of Bioethical Inquiry, March 2017
|
DOI | 10.1007/s11673-017-9771-3 |
Pubmed ID | |
Authors |
Wendy Lipworth, Paul H. Mason, Ian Kerridge, John P. A. Ioannidis |
Abstract |
Biomedical innovation and translation are increasingly emphasizing research using "big data." The hope is that big data methods will both speed up research and make its results more applicable to "real-world" patients and health services. While big data research has been embraced by scientists, politicians, industry, and the public, numerous ethical, organizational, and technical/methodological concerns have also been raised. With respect to technical and methodological concerns, there is a view that these will be resolved through sophisticated information technologies, predictive algorithms, and data analysis techniques. While such advances will likely go some way towards resolving technical and methodological issues, we believe that the epistemological issues raised by big data research have important ethical implications and raise questions about the very possibility of big data research achieving its goals. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 16% |
United States | 3 | 16% |
Spain | 2 | 11% |
Canada | 2 | 11% |
Switzerland | 2 | 11% |
Australia | 2 | 11% |
Unknown | 5 | 26% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 12 | 63% |
Scientists | 6 | 32% |
Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 2 | 1% |
Brazil | 1 | <1% |
Unknown | 139 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 24 | 17% |
Student > Master | 23 | 16% |
Researcher | 17 | 12% |
Student > Bachelor | 17 | 12% |
Other | 6 | 4% |
Other | 27 | 19% |
Unknown | 28 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Social Sciences | 17 | 12% |
Medicine and Dentistry | 16 | 11% |
Computer Science | 14 | 10% |
Arts and Humanities | 9 | 6% |
Business, Management and Accounting | 7 | 5% |
Other | 42 | 30% |
Unknown | 37 | 26% |