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Presentation . 2023
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Presentation . 2023
License: CC BY
Data sources: Datacite
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AI and Data Visitation: Addressing challenges in data transfers in clinical research within the framework of Open Science

Authors: Francis P. Crawley;

AI and Data Visitation: Addressing challenges in data transfers in clinical research within the framework of Open Science

Abstract

The legal and ethical frameworks for innovation in data acquisition and transfer Federated data, blockchain, and quality assurance Developing instruments for improving data utility in clinical trials The views presented here are those of the speaker’s. They do not necessarily reflect those of any organisation. Francis gratefully acknowledges the work Ukraine Clinical Research Support Initiative (UCRSI), of the International Science Council’s CODATA International Data Policy Committee (IDPC), and the EOSC-Future / RDA Artificial Intelligence & Data Visitation Working Group (AIDV-WG). Francis’ EOSC Future / RDA Ambassador for Ethics & Law and the EOSC-Future projects are co-funded by the European Union’s Horizon Programme call INFRAEOSC-03-2020 - Project ID 101017536. CODATA is funded by the International Science Council (ISC) and Horizon Europe as well as by other funding organisations. The Research Data Alliance (RDA) is funded by Horizon Europe as well as by other funding organisations (see here). Francis is grateful for the support provided by CODATA and the EOSC-Future and the RDA communities, structures, and secretariats.

Keywords

Artificial Intelligence, Data Visitation, Clinical Trials, Data policy, COVID, Open Science, UNESCO, Ethics, Law, Science Policy

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selected citations
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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.
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