Data skills for analysts in contemporary social survey research |
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| Coordinator 1 | Dr Vanessa Higgins (UK Data Service/University of Manchester) |
Survey analysts are experiencing a rapidly advancing data skills landscape. There is a need for the development of traditional survey data skills for contemporary research needs, while recognising growing potential for integrating survey data with an expanding array of other sources such as web data, streaming data and administrative data. More data are moving into TREs, with data access requiring additional sets of skills to those required for traditional modes of data sharing. Computing power means that new types of analyses are possible, with computational social science and machine learning developing at pace. New conversations are being had and cutting-edge work is being done on synthetic data, and while AI for coding and analysis is bringing new uses, there are concerns about verifiability and reproducibility. All this means new skills are needed, and these are constantly evolving.
The aim of this session is to create a space to share ideas around the development of data skills for analysts in contemporary social science research. We invite submissions on the development of data skills on topics such as:
- managing, accessing and analysing survey data
- new or alternative sources of data
- linking survey data with new or alternative sources of data
- teaching/training in contemporary data skills
- the use of learning technologies and software
Papers need not be restricted to these specific examples