UK Statistical System UK Statistics Authority Code of Practice
MOJ

“Wouldn’t it be cool if…

…we could look at this against x! And y. And maybe a, b and c too…”

This felt like quite a common conversation with my team, back when I was analysing data in the Department for Digital, Culture, Media and Sport (DCMS) circa 2015.

The number of interesting questions and analyses we could do with our data, if we could only put it together with other data, felt potentially limitless. And what an amazing benefit these analyses could have to society – we’d basically be able to understand and improve everything!

But it wasn’t meant to be. We did try and match our survey data with data held by one other department and… it was painful! It took months to get to the point of being able to physically share and receive data and, once we had some data, getting it ready to analyse proved tricky too. In fact, it proved so difficult that, I’m ashamed to admit, I moved roles before I managed it.

OSR also continues to emphasise the power of linked data to produce better statistics. On paper, linking data sets might sound simple but, in practice, it is often difficult. This is why I’m so excited about the recent work we’ve seen from the Ministry of Justice (MoJ). MoJ is taking great steps to link up the administrative data sets it generates in its operational work, and to make them available for analysis by people outside of the department. This means that MoJ, and other interested parties, can more easily do analysis across different parts of the justice system, and beyond, to understand the journeys individuals take.

There are two projects I’d like to highlight:

         1. Data First

In collaboration with ADR UK (Administrative Data Research UK), MoJ is undertaking an ambitious data linkage project called ‘Data First’. OSR’s 2018 review of The Public Value of Justice Statistics highlighted the need for statistics that move from counting people as they interact with specific parts of the justice system to telling stories about the journeys people take. Data First is doing just that! It will anonymously link data from across the family, civil and criminal courts in England and Wales, enabling research on how the justice system is used and enhancing the evidence base to understand ‘what works’ to help tackle social and justice policy issues.

In June, we were delighted to hear that Data First reached its first major milestone. The first, research-ready dataset – a de-identified, case-level dataset on magistrates’ court use – was made available for accredited researchers through the Office for National Statistics (ONS) Secure Research Service (SRS). This data provides insight into the magistrates’ court user population, including the nature and extent of repeat users. It enables, for the first time, researchers to establish whether a defendant has entered the courts on more than one occasion and will drive better policy decisions to reduce frequent use of the courts. In August, a second output followed, this time a de-identified, research-ready dataset on Crown Court use. This dataset is also available through the SRS.

         2. Data shares with the Department for Education (DfE)

To improve understanding of the potential links between individual’s educational outcomes and characteristics and their involvement or risk of involvement with crime and the criminal justice system, MoJ and DfE have created a de-identified, individual-level dataset, which links data from the Police National Computer (MoJ) and the National Pupil Database (DfE)[1]. The DfE data spans educational attainment, absence from school, exclusions and characteristics like special educational needs and free school meals eligibility. The MoJ data includes information on criminal histories and reoffending, court proceedings, prison and assessments of offenders. Linking this data will allow analysis that has previously not been possible, including: longitudinal analysis of trends in individual’s characteristics and outcomes; analysis to inform the design of policies and processes that better support those at risk; and evaluations of the effectiveness of interventions. Accredited researchers can apply to access the data via the ONS SRS or MoJ’s Justice MicroData Lab.

This work follows The Children in Family Justice Data Share (CFJDS)[2], which started in 2012 and has resulted in a database of child-level data linked from across the MoJ, DfE and the Children and Family Court Advisory and Support Service (Cafcass). The CFJDS provides, for the first time, longitudinal data on the short and medium-term outcomes for children who experience the family justice system. The data are being used to build understanding of how different experiences and decisions made within the family court can impact on children’s educational outcomes, and subsequently, their life chances. In turn, they will provide more robust evidence on which to make policy decisions for children and their families.

What’s really exciting about both these projects is the way that the teams involved are tackling the challenges of data linkage. Instead of creating a big new IT system to try and join up the data, these projects are starting from a position of, “let’s take what’s in the current databases and see what we can get through anonymised matching.” The exact tools used vary between teams and departments but include established tools such as SAS Data Management Studio and SQL Server Management Studio (SSMS), which were used by MoJ and DfE respectively for linking crime and justice and NPD data. For data linkage done as part of Data First, MoJ have developed a new tool called Splink, which was written in the programming language Python. Splink is an open source library for probabilistic record linkage at scale: it’s free, and MoJ hope others in government (and beyond) will find it useful for their own data linkage and deduplication tasks. Rule based matching algorithms, including ‘fuzzy-matching’ algorithms – rules used to link data based on non-perfect matches between data variables – have been used to link individuals within and between data sets.

These projects show what can be achieved when government departments, agencies and external organisations work together, and will help us start to achieve what my team and I hoped we could back in 2015. They will enable us to better understand individuals and society and, in turn, to make better decisions and policies, which will improve the justice system and outcomes for all individuals. I’m looking forward to seeing what comes next.

 

[1] To ensure the confidentiality and protection of data about children, access to DfE data extracts from the NPD is managed through tightly controlled processes.

[2] https://www.gov.uk/government/statistics/family-court-statistics-quarterly-october-to-december-2017, published 29 March 2018

A robot by any name?

My big problem with my favourite innovation of the year – the Reproducible Analytical Pipeline (RAP) – is this: what should I call it for my end of year blog? The full name is a mouthful, yet its acronym doesn’t give much of a clue to what it does.

I wanted to name it Stat-bot. I imagine a cute little droid about 3 feet tall, soppy and warm-hearted, buzzing around the Government Statistical Service dispensing help and advice wherever humans need it. But the Office for Statistical Regulation due diligence department* reviewed the blog and pointed out the existence of a commercial product with this name (also, I’m probably overly influenced by my children, who find anything including the word ‘bot’ automatically hilarious). I therefore edited this blog and used a variety of alternative imaginary names for the product.

I heard about, er, Auto-stat from Steve Ellerd-Elliot, the excellent Head of Profession for Statistics at the Ministry of Justice (MOJ). He was describing their new approach to producing statistical releases and their associated commentary using the Reproducible Analytical Pipeline (RAP).

This new approach, developed in partnership with the Government Digital Service, involves automating the process of creating some of the narrative, the highlights, the graphs and so on. It’s based on algorithms that work the basic data up into a statistical release. To find out more about how RAP works, read the Data in Government blog and this follow-up post. And to be clear, it’s not just Steve and his MoJ team that are using this approach – it was developed in the Department for Digital, Culture, Media & Sport and has been picked up by the Department for Education, amongst others. The Information Services Division in Scotland have developed a similar tool.

Like the statistical R2D2 of my imagination, this approach helps human statisticians, and in two really important ways. Firstly, Stat-O reduces the potential for human error – transposition and drafting mistakes and so on. But more significantly, robostat (?) frees up a massive amount of time for higher level input by statisticians – the kind of quality assurance that spots anomalous features in the data, narrative that links up to other data and topics, and adds human interest to the automated release.

The other thing about … statomatic? … is that it is just the most eye-catching of a broader range of innovations Steve and his colleagues at MoJ have brought to statistics in recent months. They include:

  • a new portal for prisons data, with embedded data visualisations that radically extends what the existing gov.uk web platform can host;
  • an associated suite of Justice data visualisation tools that are freely available to users: and
  • new developments within the Justice Data Lab to allow a wider range of analysis, with the pilot of a Justice MicroData Lab to open up access to the data.

When we launched the Office for Statistics Regulation we aimed to stand up for the public value of statistics. To set the standards for producing and publishing statistics; to challenge when these standards are not met, and celebrate when they are. I hope we’ve balanced challenge and celebration in a sensible way through the year and through our Annual Review.

But it’s often the way of things that the challenge attracts the most attention. So I think it’s appropriate for me to make my final blog of 2017, in what is after all a season of celebration, something of a toast to — er — I mean, a toast to — um– oh well, a toast to RAP.

 

*the due diligence department doesn’t actually exist; it was a colleague in the pub who told me about the commercial product.