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The research software engineering (RSE) survey dataset (2016-2022): A longitudinal and international resource for
Wioleta Kijewska1, Heather S Packer1, Simon Hettrick1,2
1University of Southampton, University Road, Southampton SO17 1BJ, United Kingdom.
The Research Software Engineering (RSE) Survey offers longitudinal data from 2016-2022, detailing demographics, work practices, and job satisfaction for RSEs globally. This valuable dataset supports workforce analysis and reproducible research.
Area of Science:
- Computer and Information Science
- Social Sciences
Background:
- The Software Sustainability Institute has collected longitudinal survey data on Research Software Engineers (RSEs) from 2016 to 2022.
- The survey initially focused on the UK and expanded internationally, using a standardized instrument from 2018 onwards for comparability.
Purpose of the Study:
- To provide a comprehensive dataset on the RSE workforce, covering demographics, employment, technical practices, and job satisfaction.
- To enable longitudinal and cross-country analyses of the RSE profession.
- To support reproducible research through openly available data and analysis code.
Main Methods:
- Longitudinal survey design collecting data between 2016 and 2022.
- International data collection with a standardized instrument from 2018.
- Voluntary participation open to individuals identifying as RSEs or performing research-software-related work.
Main Results:
- The dataset includes anonymized responses on demographics, employment, coding practices, training, collaboration, publications, sustainability, networks, and job satisfaction.
- An interactive dashboard allows exploration of trends, cross-country comparisons, and changes across survey waves.
- The data supports workforce comparisons and integration with external datasets.
Conclusions:
- The RSE Survey dataset is a valuable, openly licensed resource for understanding the global RSE workforce.
- Its longitudinal and international scope facilitates diverse research applications, including temporal and comparative analyses.
- Future surveys, including the upcoming 2026 survey, will expand the dataset, ensuring its continued relevance.
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