Data News

Last year, a successful Turing-LIDA Data Study Group took place – an intensive two-week hackathon with 62 researchers, at different stages of their careers and from a number of different countries, rising to one of six challenges set by different organisations. Some amazing research was done in a very short time, and five of the six reports into their findings have now been published:

Sainsbury’s – Investigating the impact of the UK’s Soft Drinks Industry Levy on consumers’ purchases of soft drinks

Morrisons – Optimising the supply chain to minimise waste and delivery mileage

Asda – Exploring and quantifying the effect of weather on sales

Ordnance Survey Northern Ireland – Leveraging LiDAR and Street View data for road feature detection

Network Rail – Automatic detection of counterfort drains

Data Study Groups are a perfect opportunity for organisations (Challenge Owners) to test questions/problems quickly and with minimal resource, gaining insight into potential ways to further develop those areas of research.  They also give researchers, at all stages of their careers, the chance to collaborate with others from different institutions and different disciplines, and apply their knowledge to real-world problems.  For more information, visit The Alan Turing Institute’s Data Study Groups page.

CDRC have recently replaced our venerable map website, CDRC Maps, with CDRC Mapmaker! This new flexible repository for visualising many of CDRC’s open datasets, was initially developed by Geolytix and further augmented by our own developers. The website is backed by the CARTO data platform and is cloud hosted.

Web mapping technology has come a long way since CDRC Maps was first released in 2015, with responsive, multi-platform high resolution mapping now commonplace, and CDRC wants to take advantage of these advances to create a better way of visualising our many datasets. Using a new platform also simplifies CDRC’s own processes for adding new maps, allowing our researchers to manage their map configuration using GitHub, and add and update their data using CARTO’s web-based front-end to its data platform. The “command line” is no longer needed to produce maps, and the power of the cloud ensures that our maps remain visible to the world regardless of university infrastructure changes or local issues.

Technical users might be interested to know that the website is built in ES6 JavaScript, using the Vue, Mapbox GL and Bootstrap frameworks, and built and deployed using npm and GitHub. The data is delivered to your browser in the Mapbox Vector Tiles (MVT) format.

The website is structured around presenting two types of maps – metric maps (which show various continuous variables associated with a particular dataset, sliced into groups) and classification maps which categorise areas into a single value (sometimes with a hierarchy of levels) and generally include a pen portrait description of the category.

Users can filter maps based on one or more classification categories or on multiple metric value ranges, and a PDF report can be easily produced with a view of the current map, a key and accompanying text and direct link. Clicking many of the maps will not only present the metrics or portrait, but include statistics on proportions in the current administrative area or a custom drawn region. The user interface is deliberately simple with standard pan/zoom controls, map selector, postcode search and layer toggles – that’s it. 

For our initial release of Mapmaker, there are around 30 maps, covering CDRC classifications such as Consumer Vulnerability and the Internet User Classification (IUC), CDRC metric products such as Access to Healthy Assets and Hazards (AHAH) and Residential Mobility (Churn), and some popular government datasets like the Index of Multiple Deprivation (IMD), VOA building ages and Ofcom broadband speeds/availability. Some of our legacy maps remain on the old CDRC Maps platform which can still be accessed through a special menu option.

We plan to continue to refine and improve CDRC Mapmaker, including a tighter integration with our main CDRC Data platform soon, and make fuller use of the CARTO data platform as a canonical data store for our outputs. 

We hope CDRC Mapmaker forms a useful visualisation tool for some of CDRC’s many data assets, and its filtering and reporting functionality allow CDRC’s data to be viewed and used in new ways.

With our data partner Registry Trust, CDRC can provide access to data on County Court Judgements, which offer a key measure of financial health, both at an individual level, and also at an area and country level. The data are available County Court Judgements, either at an aggregated level (MSOA and Local Authority District) as a Safeguarded product or aggregated to LSOA level and at individual Judgement level as a Secure data product.

These data can be used as input data to a wide range of analyses looking at financial health and a range of other factors. Millie Corless, Data Analyst at Registry Trust, works with these data and performs a wide variety of analyses. However, she only has limited time available to analyse these data, so there are many more potential projects that could be done, with some examples listed below and on the data page.

Prior to working at Registry Trust, Millie completed her masters dissertation through the CDRC Masters Dissertation Scheme (MDS), working with the Registry Trust, which gave her the time to analyse the data in new and interesting ways. Millie is very interested in health and she looked at the CCJ data and explored its relationship with health.

Her dissertation project assessed geographic and temporal patterns in consumer (individual level) County Court Judgment (CCJ) rate (as an indicator of financial vulnerability), and considered the extent to which general health influences personal financial vulnerability across England and Wales. The project then considered the influence of additional socio-economic variables, such as Tenure and Employment Status, on financial vulnerability. The outcomes highlighted spatio-temporal locales where specific socio-economic variables influence financial vulnerability more, thus where the implementation of health improving policy will tackle the instability. More details available on her blog post.

There are a number of potential topics listed on the CDRC Data page that could be undertaken with CCJ data. These would make a good Masters Dissertation project (Registry Trust will be offering projects through the MDS) or you are welcome to apply to access the data and complete a different project independently.

Potential projects could include:

• Work on a way to derive and publish a set or range of economic health indicators
• Predict the future trend of these economic health indices
• Use data to highlight exceptions and process inefficiencies in public sector entities e.g. exception reporting on court timelines, outcomes that are outside expected benchmarks, highlighting court inefficiencies, bottlenecks or process flaws
• Improve existing data accuracy and gaps, e.g. impute missing or inaccurate data
• Explore issues around CCJs and fraud – tackle the myth of the ‘unsound’ CCJ
• Look at the effect of politics on indebtedness – what relationships are there between Government, national political representation, local representation and indebtedness?
• Develop the Financial Stress Tracker produced by Registry Trust, to include the self-employed, those on low income, those who have been impacted by COVID and other factors.
• Focus solely on Scotland or Northern Ireland, as these regions have had less focus at Registry Trust.
• Get a closer insight into those taking out a judgment, for example which are the most forthright? Why might this be? Are there spatial or temporal trends?

If you are interested, or would like more information, please either reach out to Millie directly (m.corless@registry-trust.org.uk) or email CDRC (info@cdrc.ac.uk).