Strand Leader: Professor Dr Alexandru Cernat (University of Manchester)
Recent years have seen an explosion of non-survey data sources that provide an unprecedented amount of information about populations and the communities they reside in and have the potential to help address some of the challenges facing surveys. These sources include geospatial data, satellite imagery, and administrative data. However, approaches to mobilising, integrating, and leveraging these non-survey data assets into survey programmes require development.
RS7 will conduct a systematic literature review and develop a typology of non-survey data sources that have been integrated with surveys, as well as those that would be likely possible and useful to be integrated with a range of UK surveys. We will review what is known about the quality aspects of these data sources, including their coverage, selection, and measurement properties, and review proposed data quality indicators and correction methods. This work will feed into the development of a report cataloguing the different data integration options available to survey practitioners, and describing their associated data quality implications and, where available, potential quality improvement strategies. Through a series of diverse case studies, we will demonstrate and evaluate how non-survey data can be integrated and leveraged for specific survey data collection activities, namely: 1) evaluating and correcting for nonresponse bias; and 2) monitoring and intervening in survey data collection. The case studies will be written up as practical reports for survey researchers, highlighting the potential uses and opportunities of data integration across a range of survey sectors. The reports will be accompanied with companion “how-to” guides providing a generic framework for implementing the data integration methods for each of the above survey activities.