Introduction to using linked data between the Ministry of Justice and Department for Education - Online


20/11/2024 - 21/11/2024

Organised by:

NCRM, University of Southampton


Dr Alice Wickersham


Intermediate (some prior knowledge)


Jacqui Thorp
Training and Capacity Building Coordinator, National Centre for Research Methods, University of Southampton

video conference logo

Venue: Online


This course is run as a collaboration between the National Centre for Research Methods and Administrative Data Research UK and is part of a series on short courses on administrative data.

This short online course provides an introduction to an existing data linkage between the Ministry of Justice and Department for Education, with a particular focus on the Police National Computer (PNC) and National Pupil Database (NPD). The course will include a mixture of lectures, interactive sessions, and practical exercises to put learning into practice.

The course covers: 

  • Accessing the data share

  • Overview of available data 

  • Tips and considerations for data cleaning

  • Successfully clearing outputs

  • Case studies using the linked dataset

By the end of the course participants will:

  • Know how to access the data share
  • Be familiar with the content of the data
  • Know how to navigate some data cleaning challenges
  • Understand some strengths and limitations of the data
  • Know how to create successful outputs for clearance

This course will suit anyone interested in conducting quantitative data analyses using linked education and crime data in England. This may include, but is not limited to, quantitative researchers in academic, government, or third sector settings. People at any stage in their research career would be welcome, but the course will likely most interest PhD students, early career researchers, and mid career researchers.  

No specialist prior knowledge of the NPD, PNC, or statistical software is needed to attend, but a basic knowledge of research design and quantitative data analysis would be beneficial.

No prior reading is required for this training, but applicants may wish to explore existing outputs arising from the NPD and PNC, such as:


Programme - TBC

Day 1:

  • Introduction/housekeeping (lecture) (30 mins)
  • Accessing the data (lecture and group practical) (1 hour)
  • Break (15 mins)
  • Overview of available data (lecture and interactive session) (1.5 hours)
  • Q&A (15 mins)

Day 2:

  • Tips and considerations for data cleaning (lecture and group practical) (1.5 hours)

  • Break (15 mins)

  • Successfully clearing outputs (lecture and group practical) (1.5 hours)

  • Q&A (15 mins)


The fee per teaching day is: • £35 per day for registered students at any University. • £75 per day for staff at academic institutions, Research Councils researchers, public sector staff, staff at registered charity organisations and recognised research institutions. • £250 per day for all other participants In the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. No refunds are available after this date. If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of the cancellation of a course. The University of Southampton’s Online Store T&Cs also continue to apply.

Website and registration:


South East


Longitudinal Research , Analysis of administrative data, Data Quality and Data Management , Quantitative Data Handling and Data Analysis, Interdisciplinary and Multidisciplinary Research, Data Linkage

Related publications and presentations:

Longitudinal Research
Analysis of administrative data
Data Quality and Data Management
Quantitative Data Handling and Data Analysis

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