PU-23-0114

Award outcome

Description

ONS is seeking to develop partnerships with organisations that hold information about mobility data in the UK. We are looking to use the data for a) understanding population domestic travel by travel purposes (specifically commuting trips) and transport modes (highly desirable to distinguish at least car, bus/tram, rail/metro, walk, cycle) at fine geographical scale (MSOA and ideally LSOA) and high frequent temporal dimension (Weekly, monthly, etc.) and b) understanding international migration (foreign travelers travel) and travel and tourism (UK Population Travel). We would be looking to use the data for validation and calibrating journey to work and Travel and Tourism models through fusing mobility data with other surveys and admin data sources and make the resulting anonymized and aggregated series publicly available on our website as part of a regular release. As well as publishing aggregate information, we are also interested to understand if organisations would support the sharing of microdata across government departments. The data will need to include as a minimum: · Journey counts by travel purpose and mode. · Population counts at homeplace, workplace, visit and where available other purposes. · trip duration and trip distance. · Low-level geography classification (MSOA at a minimum, or preferably lower level such as LSOA or information to be able to derive this in-house). · Travel purpose (should distinguish at least home to work, home from work, and ideally home to school, home from school, and any further individual travel purposes that could reliably be derived, while distinguishing each of to home; from home; or non- home-based, for such purposes). Mode of transport (highly desirable to distinguish at least car, bus/tram, rail/metro, walk, cycle) - some aggregation of mode can be acceptable if there are methodology limitations for inference. · Delivery Frequency (Weekly, Monthly). · Temporal resolution (Daily, Weekend Period, Weekday Period, Weekly, Monthly, Annual). · Historic data (specifically over the Census 2021 month) to enable quality assurance. · Meta Data and detailed methodology report with a mechanism for quality assurance. PLEASE VIEW ATTACHEMENT DOCUMENT FOR FURTHER INFORMATION.

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