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The UK Data Service Data Skills Framework for working with large scale survey data, census, and macro-level aggregate data

Authors: Higgins, Vanessa; Price, Debora; King-Hele, Sarah;

The UK Data Service Data Skills Framework for working with large scale survey data, census, and macro-level aggregate data

Abstract

In this discussion paper, we present an analysis of the training landscape in the UK for social, population and economic data, and we propose to the Social Science Data Training Community a Data Skills Framework for working with these kinds of data. This Framework has been developed in the context of a data landscape undergoing unprecedented change at rapid pace. We envisage it as a live and evolving piece of work, and very much welcome discussion on the content. This initiative aims to establish a robust framework for developing essential data analysis skills for the social, economic and population sciences, focusing on large-scale survey, census, and macro-level aggregate data characteristic of the UK Data Service (UKDS) holdings. The framework acknowledges a rapidly advancing data skills landscape. It emphasises continued development of traditional data skills for contemporary research needs, while recognising growing potential for integrating survey or census data with an expanding array of other sources increasingly accessible to social scientists, as well as promising opportunities presented by AI and machine learning for enhancing analysis. The paper is authored by Dr. Vanessa Higgins, Service Director for Training and User Support, Professor Debora Price, Deputy Director of the UK Data Service, and Dr. Sarah King-Hele, Research Fellow and Training Manager, UK Data Service. Dr Vanessa Higgins https://orcid.org/0000-0003-1694-9096 Professor Debbie Price Debora Price (0000-0003-3398-6083) - ORCID Dr Sarah King-Hele

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United Kingdom
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citations
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!
1
Average
Average
Average
Green