| Summary: | The Ministry of Justice (MoJ) Data First Synthetic Data Project aims to improve engagement with Data First datasets by making synthetic versions of content available to enable more rapid development of research proposals and to thereby enhance the potential for linked administrative data to improve understanding and outcomes across justice systems. The project has led the development of two components: a dataset generation platform and an initial release of lo-fidelity, synthetic data tables. This study includes a synthetically-generated version of the Ministry of Justice Data First Civil Courts datasets. Synthetic versions of all 43 tables in the MoJ Data First data ecosystem have been created. These versions can be used / joined in the same way as the real datasets. As well as underpinning training, synthetic datasets should enable researchers to explore research questions and to design research proposals prior to submitting these for approval. The code created during this exploration and design process should then enable initial results to be obtained as soon as data access is granted. The Ministry of Justice Data First civil court dataset provides data on civil justice cases heard by the county courts in England and Wales from 2012. Data has been extracted from the CaseMan and Possession Claims Online (PCOL) management information systems, used by His Majesty's Courts and Tribunals Service (HMCTS) to manage civil law cases within the county courts. Information is included on individual civil actions (including money claims, damages, bankruptcy, and mortgage and landlord possession cases); the people involved as parties to the case and their role; and key case dates, processes and outcomes (such as monetary amounts awarded in judgments). There are separate tables for cases or claims, parties, events in the case, hearings, judgments and warrants, which can be joined together. A civil case will usually have multiple people or companies involved (for example a claimant and defendant) and may have many events, which are each included as a separate record. These depend on the type of case and its progress. As part of Data First, records have been de-identified and deduplicated, using our probabilistic record linkage package, Splink, so that a unique identifier is assigned to all records believed to relate to the same person, allowing for longitudinal analysis and investigation of repeat appearances. This opens up the potential to address questions on, for example, common transitions between different civil actions and patterns associated with repeat involvement in the civil court system.
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