Research objectives and summary findings
Disclaimer: Within this report, we aim to portray the views of participants and to reflect their words as closely as possible. The findings that are presented therefore reflect the opinions and experiences of a range of individuals and may not be shared by others within the same or other institutions, including the Office for National Statistics. Some quotes have been edited for language and grammar to improve accessibility, without changing the content or meaning.
The UK Statistics Authority’s (UKSA) Online Inclusive Data Consultation was open to the public for 12 weeks from 5 January to 26 March 2021. Its purpose was to support the work of the Inclusive Data Taskforce in considering how best to ensure that:
“…our statistics, [analysis and publications] reflect the experiences of everyone in our society so that everyone counts, and is counted, and no one is forgotten.” (UKSA strategy – Statistics for the Public Good, 2020)
We consulted to gain views on:
- what was needed to improve the inclusivity of UK data and evidence, such as:
- where there are data and evidence gaps
- where data and evidence are currently lacking or partial (regarding topics and quality)
- where further work is needed
- where to make improvements and what is currently working well
Theme-based analysis of responses generated four main themes, each with two sub-themes, in relation to the inclusivity of data and evidence across the UK. These consisted of accessibility of data, inclusivity of methodological practices, inclusivity of existing data and evidence, and trust, transparency and engagement. Within these themes, there were several issues which were common across both individuals and those responding on behalf of an organisation.
Participants identified some problems with the accessibility of data and evidence needed for research purposes because:
- it was not freely available
- it was not available quickly enough to keep up with current topics
- concise data was difficult to access due to being spread across a variety of statistical organisations and their sources, for example, websites and datasets; users must access each source separately to obtain the required data
- data were identified as not being user friendly, such as being presented unanalysed in Excel, or not designed to support people with visual impairments
Inclusivity of methodological practices were also seen as important to address. The classifications used in survey questionnaires was seen as one of the main challenges for data collection. Relying on quantitative data alone to explore complex inclusivity topics was also raised as an issue. Using qualitative or mixed methods, which would enable deeper understanding of people’s experiences and the circumstances that influence representation and inclusion, was suggested.
In terms of the inclusivity of existing data and evidence, specific data gaps were identified. These mainly related to digital poverty, socioeconomic inequality, education and housing inequalities, and disability. These gaps were said to result in:
- under-representation of groups
- a lack of granularity within the data (particularly for dimensions which overlap)
- an inability to address relevant issues and inequalities
Issues around geographical coverage at the local, national, and international level were outlined, including insufficient coordination and consistency to enable effective comparability between areas.
Finally, trust, transparency and engagement were also considered important by participants. Some participants believe that research agencies lack trustworthiness, and distrust was cited as a major barrier, preventing the participation of certain groups in data collection. One reason provided for this was a lack of transparency within research processes, for example, not explaining:
- why data are collected
- how data may be shared
- the process of data collection itself
Previous engagement and consultation activities were appreciated, but several participants felt that further efforts were needed, with a focus on collaboration and follow-up action. Inclusion and representation are considered essential, especially for those often excluded from data collection.Back to top