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Other literature type . 2024
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Presentation . 2024
License: CC BY SA
Data sources: Datacite
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Presentation . 2024
License: CC BY SA
Data sources: Datacite
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PRUK UKDS: Introduction to Synthetic Data for Longitudinal Data Managers Workshop

Authors: Kasmire, Jools; Magder, Cristina; UK Data Service; Economic and Social Research Council; Medical Research Council; University of Essex; University of Manchester;

PRUK UKDS: Introduction to Synthetic Data for Longitudinal Data Managers Workshop

Abstract

This record contains materials from the interactive workshop, Introduction to Synthetic Data for Longitudinal Data Managers, hosted by the UK Data Service (UKDS) as part of the PRUK UKDS Skills Development for Managing Longitudinal Data for Sharing Project. The workshop aimed to introduce data managers and their colleagues to the fundamentals of synthetic data, including its potential for enhancing data management and sharing in longitudinal and biomedical studies. The workshop was designed to provide practical and theoretical insights into synthetic data through interactive presentations, live coding demonstrations, and Q&A sessions. The workshop covered: An introduction to the Skills Development for Managing Longitudinal Data for Sharing project, funded by the Economic and Social Research Council (ESRC) and the Medical Research Council (MRC), as part of an initial Population Research UK (PRUK) initiative. Key concepts of synthetic data, including its definitions, types, use cases, and generation methods. A live coding demonstration using Jupyter notebooks to showcase synthetic data generation techniques in Python. The uploaded files include: introtosyntheticdata_2024-10-14.pdf Presentation by Cristina Magder: Introduction to Synthetic Data for Longitudinal Data Managers introtosyntheticdata_JK_2024-10-14.pdf Presentation by Dr. Jools Kasmire: Synthetic Data: An Introductory Workshop. Participants were also provided access to: Jupyter notebooks used in the live coding session. Supplementary resources via a GitHub repository (link provided during the workshop). This workshop was tailored for: Longitudinal data managers. Other data professionals interested in leveraging synthetic data for ethical and effective data sharing. These materials were created under the Skills Development for Managing Longitudinal Data for Sharing project, funded by the Economic and Social Research Council (ESRC) and the Medical Research Council (MRC). They are intended for individuals seeking to improve their research data management practices and for trainers delivering similar content.

Keywords

Synthetic Data, Data Sharing, Ethical Data Practices, Data Privacy, Research Data Management, Longitudinal Data, Data Training

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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).
BIP!Citations provided by BIP!
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!
0
Average
Average
Average
Green