Cross-Sectoral Big Data: The Application of an Ethics Framework for Big Data in Health and Research.
Clicks: 364
ID: 62381
2019
Article Quality & Performance Metrics
Overall Quality
Improving Quality
0.0
/100
Combines engagement data with AI-assessed academic quality
Reader Engagement
Star Article
82.6
/100
361 views
294 readers
Trending
AI Quality Assessment
Not analyzed
Abstract
Discussion of uses of biomedical data often proceeds on the assumption that the data are generated and shared solely or largely within the health sector. However, this assumption must be challenged because increasingly large amounts of health and well-being data are being gathered and deployed in cross-sectoral contexts such as social media and through the internet of (medical) things and wearable devices. Cross-sectoral sharing of data thus refers to the generation, use and linkage of biomedical data beyond the health sector. This paper considers the challenges that arise from this phenomenon. If we are to benefit fully, it is important to consider which ethical values are at stake and to reflect on ways to resolve emerging ethical issues across ecosystems where values, laws and cultures might be quite distinct. In considering such issues, this paper applies the deliberative balancing approach of the (Xafis et al. 2019) to the domain of cross-sectoral big data. Please refer to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end.
Abstract Quality Issue:
This abstract appears to be incomplete or contains metadata (189 words).
Try re-searching for a better abstract.
| Reference Key |
laurie2019crosssectoralasian
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Laurie, Graeme T; |
| Journal | Asian bioethics review |
| Year | 2019 |
| DOI |
10.1007/s41649-019-00093-3
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.