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Biomedical Big Data: New Models of Control Over Access, Use and Governance

Overview of attention for article published in Journal of Bioethical Inquiry, October 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#34 of 658)
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
40 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
79 Dimensions

Readers on

mendeley
191 Mendeley
Title
Biomedical Big Data: New Models of Control Over Access, Use and Governance
Published in
Journal of Bioethical Inquiry, October 2017
DOI 10.1007/s11673-017-9809-6
Pubmed ID
Authors

Effy Vayena, Alessandro Blasimme

Abstract

Empirical evidence suggests that while people hold the capacity to control their data in high regard, they increasingly experience a loss of control over their data in the online world. The capacity to exert control over the generation and flow of personal information is a fundamental premise to important values such as autonomy, privacy, and trust. In healthcare and clinical research this capacity is generally achieved indirectly, by agreeing to specific conditions of informational exposure. Such conditions can be openly stated in informed consent documents or be implicit in the norms of confidentiality that govern the relationships of patients and healthcare professionals. However, with medicine becoming a data-intense enterprise, informed consent and medical confidentiality, as mechanisms of control, are put under pressure. In this paper we explore emerging models of informational control in data-intense healthcare and clinical research, which can compensate for the limitations of currently available instruments. More specifically, we discuss three approaches that hold promise in increasing individual control: the emergence of data portability rights as means to control data access, new mechanisms of informed consent as tools to control data use, and finally, new participatory governance schemes that allow individuals to control their data through direct involvement in data governance. We conclude by suggesting that, despite the impression that biomedical big data diminish individual control, the synergistic effect of new data management models can in fact improve it.

X Demographics

X Demographics

The data shown below were collected from the profiles of 40 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 191 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 191 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 35 18%
Researcher 31 16%
Student > Ph. D. Student 16 8%
Student > Doctoral Student 12 6%
Student > Bachelor 10 5%
Other 23 12%
Unknown 64 34%
Readers by discipline Count As %
Social Sciences 24 13%
Computer Science 18 9%
Medicine and Dentistry 15 8%
Biochemistry, Genetics and Molecular Biology 9 5%
Business, Management and Accounting 8 4%
Other 41 21%
Unknown 76 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 36. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 June 2021.
All research outputs
#1,098,797
of 25,162,879 outputs
Outputs from Journal of Bioethical Inquiry
#34
of 658 outputs
Outputs of similar age
#22,524
of 328,745 outputs
Outputs of similar age from Journal of Bioethical Inquiry
#3
of 12 outputs
Altmetric has tracked 25,162,879 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 658 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 328,745 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.