Magistrates’ court dataset is first product of Data First programme available to researchers
Categories: Data linkage programmes, ADR England, Office for National Statistics, Crime & justice
30 June 2020
A de-identified, research-ready dataset on magistrates’ court use has today (30 June 2020) become the first to be deposited in the Office for National Statistics (ONS) Secure Research Service (SRS) as a result of the Ministry of Justice’s ADR UK-funded Data First programme. The dataset is now available to be accessed by accredited researchers.
The ‘magistrates’ court defendant case level dataset’ is supported by a suite of materials to enable accredited researchers – across government and academia – to make the best of use of this data to improve our understanding of justice-system use. These resources include a Data First user guide and data catalogue, which describe the nature and the quality of the data shared.
Data First is a ground-breaking three-year data linking programme, led by the Ministry of Justice (MoJ) and funded by ADR UK. The project aims to unlock the potential of the wealth of data already held by MoJ, linking administrative datasets from across the justice system and beyond to better inform policy related to crime and justice.
About the data
The ‘magistrates’ court defendant case level dataset’ provides data on magistrates’ court use between 2011 and 2019. This data will provide insight into the magistrates’ court user population, including the nature and extent of repeat users. It will enable, 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.
Lord Justice Fulford, Vice President Court of Appeal (Criminal Division) and the Judicial Lead on Data, said: “I consider this to be an extremely important project, which has been established according to all of the principles that necessarily apply to work of this kind. In a sentence, it will enable critical research to be undertaken by accredited professionals, whilst protecting the identities of those involved in the individual cases.
"It is clearly vital that we make the best and the most responsible use of our invaluable data resource, without undermining the independence of the judiciary, the fair administration of justice or the privacy of those who are entitled to expect protection. I am reassured by the collaborative approach that has been adopted, and I look forward to being briefed on this developing enterprise.”
Sir Richard Heaton, Permanent Secretary for the Ministry of Justice, said: “The Data First project reflects the commitment of the Ministry of Justice to enhance our use of data and evidence to inform policy decisions and improve justice outcomes.
“The release of the de-identified magistrates’ court dataset for accredited researchers represents the first step in this ambitious programme.”
Welcoming the announcement, Susan Acland-Hood, Chief Executive of HM Courts & Tribunals Service (HMCTS), said: “Following last year’s Legal Education Foundation report and recommendations for HMCTS’ data strategy, this represents the next critical step to opening up our data to academics and accredited researchers. By providing nearly a decade of de-identified data from the Magistrates’ Court, we’re enabling independent research to be undertaken that could inform and shape future policy and service design.
“It’s a landmark moment – for HMCTS as well as ONS – and is a signal of our future intent.
“We know we have much more to do. Working with the Ministry of Justice and the judiciary, we will continue to make progress in fulfilling our commitment to being more transparent.”
How to access the dataset
Researchers seeking to access this new dataset must first become an accredited researcher by completing the relevant forms from the UK Statistics Authority and submitting them to research.support@ons.gov.uk.
If you are already an accredited researcher, you can apply to access the specific data required for your project on gov.uk.