How can we better understand the integrity (i.e. accuracy, completeness, and consistency) and use of Population Movement data?

Background

Our key focus areas, detailed in our critical policy issues and questions below, are as follows:
• How emerging and developing technologies are likely to impact the future UK geospatial ecosystem, and how best to track its adoption and use in the economy.

• Further developing our understanding and methodology for valuing location data, applications and services to the economy and society.

• Building confidence in the geospatial ecosystem – including understanding changing public attitudes and growing the future pipeline of geospatial skills.

Next steps

If you are keen to register your interest in working and connecting with DSIT Digital Technology and Telecoms Group and/or submitting evidence, then please complete the DSIT-ARI Evidence survey - https://dsit.qualtrics.com/jfe/form/SV_cDfmK2OukVAnirs.
Please view full details: https://www.gov.uk/government/publications/department-for-science-innovation-and-technology-areas-of-research-interest/dsit-areas-of-research-interest-2024

Source

This question was published as part of the set of ARIs in this document:

DSIT Areas of Research Interest 2024 GOV UK

Related UKRI funded projects

  • Developing a Census Based Generative Geodemographic Classification System

    Leveraging the power of contemporary Artificial Intelligence (AI), this project aims to revolutionize the way in which we can build and use geodemographic classifications. This will do so by enabling more accurate repres...

    Funded by: ESRC

    Lead research organisation: University of Liverpool

    Why might this be relevant?

    The project aims to revolutionize the way geodemographic classifications are built and used, providing a more accurate representation of socio-spatial structure and proposing a user-friendly online tool for creating tailored census-based geodemographic data products.

  • Using Secondary Data to Measure, Monitor and Visualise Spatio-Temporal Uncertainties in Geodemographics

    Geodemographic classifications are categorical summary measures of the built, social and economic characteristics of small geographical areas. There are many geodemographic classifications supplied by both the commercial...

    Funded by: ESRC

    Lead research organisation: University of Liverpool

    Why might this be relevant?

    Partially relevant as it focuses on geodemographics and uncertainty measures, but not specifically on population movement data.

  • Population247NRT: Near real-time spatiotemporal population estimates for health, emergency response and national security

    Decision-making and policy formulation in sectors such as health, emergency/crisis response and national security, ideally require accurate dynamic information on the number of people in specific places at specific times...

    Funded by: ESRC

    Lead research organisation: University of Southampton

    Why might this be relevant?

    Fully relevant as it addresses near real-time population estimates for health, emergency response, and national security.

  • Big, Open Data: Mining and Synthesis (BODMAS)

    The volume and assortment of available data for research in the social sciences has dramatically increased in recent years- a trend that shows no sign of stopping. For the first time researchers can obtain large amounts ...

    Funded by: ESRC

    Lead research organisation: University College London

    Why might this be relevant?

    Partially relevant as it focuses on big data mining and synthesis, but not specifically on population movement data.

  • Dynamic equation approach to forecast long-range demographic scenarios

    We live in a time of big social change: economic development and medical innovations have contributed to produce an unprecedented demographic boom that is affecting the lives of billions of people and impacting the envir...

    Funded by: EPSRC

    Lead research organisation: University of Bristol

  • CORDIAL-AI: Innovating with Large Language Models at the UK Data Service for Census Information Discovery and Retrieval using Natural Language

    The advancements of AI and the rapid growth of its use across society present both challenges and opportunities. At the UK Data Service (UKDS), we aim to explore the full potential of this technology while committing to ...

    Funded by: ESRC

    Lead research organisation: University College London

  • UK DATA SERVICE-CENSUS SUPPORT SERVICE (UKDS-CSS)

    A 'Census Programme' has been funded by the ESRC for the last decade that has enabled 'data support units' to create, maintain and develop data delivery systems that allow users in the academic community in the UK to hav...

    Funded by: ESRC

    Lead research organisation: University of Leeds

  • DEBIAS - DEveloping a framework to measure and correct BIASes in human mobility data extracted from digital footprints

    Our project, DEBIAS, aims to develop a generalisable framework to quantify and adjust existing biases in Digital Footprint Data (DFD) on human mobility. To this end, we will use DFD on human mobility obtained from users ...

    Funded by: ESRC

    Lead research organisation: University of Liverpool

  • Urban Big Data Centre

    The Urban Big Data Centre aims to promote innovative research methods and the use of big data to improve social, economic and environmental well-being in cities. Traditionally, quantitative urban analysis relied on data ...

    Funded by: ESRC

    Lead research organisation: University of Glasgow

  • Supporting Post Pandemic Recovery and Resilience through New Forms of Data

    This proposal will build a community of practice around the use of new forms of data to support post pandemic recovery and resilience, with a comparative focus on UK and South Korean neighbourhoods. Our network brings to...

    Funded by: FIC

    Lead research organisation: University of Liverpool

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