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Presentation . 2023
License: CC BY
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Presentation . 2023
License: CC BY
Data sources: Datacite
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Public engagement: Data for science and health

Authors: Emily Jesper-Mir;

Public engagement: Data for science and health

Abstract

Trustworthy data science depends on engagement with patients and the public- the communities who are affected by data science and digital tools used in healthcare and health research. Datasets, digital tools and analytics need to be designed for – and with – diverse populations, so they don’t only work for some groups at the expense of others. Our speaker from Wellcome Trust will share three examples of different approaches to engaging with patients and the public: Closing gaps in patient data for Black and South Asian communities: a nationally representative survey, community research and engagement A public guide to large datasets: cocreated with experts and members of the public An easy-read guide to NHS data: cocreated with adults with learning disabilities

This seminar was presented as part of RSF Open Seminars.

Keywords

biomedical research, open science, CC-BY

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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