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Local Data Spaces: ONS Research Excellence Project Award 2021 winners!

The CDRC’s Local Data Spaces project has been chosen as the winner of the prestigious ONS Research Excellence Project Award 2021 from the 400+ projects who used Office for National Statistics (ONS) data this year! This award recognises innovative research that has delivered public good or informed policy decisions.

The Local Data Spaces project combined ONS datasets with the CDRC’s own consumer data, creating ten innovative reports for each English Local Authority. These reports delivered highly tailored insights about how their communities were affected by the pandemic, which could then help to shape policy strategies.

For example, in Liverpool, the reports identified that sections of the community with low confidence in using internet technologies were less likely to make use of lateral flow tests. This led to local efforts to promote testing beyond social media, feeding these insights into the national roll-out of lateral flow testing that helped re-open workplaces and schools following the January lockdown.

In Norfolk, the analysis shows that furloughed workers were three times more likely to have caught COVID-19 than individuals who were employed or self-employed, suggesting that more could have been done to prevent COVID-19 outside of workplaces. A similar pattern was observed in most places nationally.

The project also found that, across England, COVID-19 did not significantly vary between men and women within different work sectors or occupations. One exception was the higher rate for COVID-19 in women employed in personal services jobs (e.g. hairdressers, barbers, cleaners, beauticians) at the start of the second wave. Findings from this work were presented to SAGE (Scientific Advisory Group for Emergencies) to help inform national policy around gender inequalities.

“The pandemic has shown the importance of getting the right data into the right hands,” said Dr Mark Green, lead researcher. “Local Data Spaces has opened up new sources of data to local authorities and helped them proactively respond to COVID-19.

“We are honoured to receive this prestigious ONS award. I am really proud of how our team worked at pace to support urgent policy needs during a global crisis.”

Professor Alex Singleton, CDRC Co-Director, added: “The strategic ESRC funding enabling the Local Data Spaces project perfectly illustrates the value and impact that can be unlocked by the social sciences when integrating consumer and government data within trusted research environments.”

Each of the 10 reports for all Local Authorities across England are freely available from the CDRC website and tackle a variety of themes related to the local impacts of COVID-19, from demographic and occupational inequalities, through excess mortality, to economic vulnerabilities.

Huge congratulations to the whole research team!!

Digitising Historical Telephone Directories with BT Archives:
GISRUK Best Short Paper Award 2021

CDRC collaborative PhD student, Nikki Tanu, and Senior Research Fellow, Dr. Maurizio Gibin, were awarded the ‘Best Short Paper’ award at the 2021 GIS Research UK (GISRUK) online conference on 16 April 2021. Their paper, ‘Georeferencing historical telephone directories to understand innovation diffusion and social change’, described pioneering work in the digital capture and georeferencing of the 1881 telephone directory. The work demonstrates proof of concept that will be rolled out to digitise selected directories up to the 1980s and will make it possible to chart the spatial and social diffusion and use of fixed line telephony in the 19th and 20th centuries.

Process of optical character recognition and geocoding used on the telephone directories

CDRC researcher Meixu (May) Chen was joint winner of the Sinesio Alves Junior Prize (https://www.ucl.ac.uk/bartlett/casa/remembering-sinesio-alves-junior) for work undertaken whilst she was working at CDRC in Liverpool.

Congratulations to May, Maurizio and Nikki!

(Written by Dr Nick Bearman, Project Delivery Manager, and originally posted on www.data.cdrc.ac.uk)