Training: Open science and practical data management for reproducible research

This short course (delivered on two mornings over two days) will cover the basics of open science principles and data management. It is delivered by the Education and Child Health Insights (ECHILD) team at UCL Great Ormond Street Institute of Child Health.

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Day one focuses on the principles of open science and reproducible research, from project inception through to analysis, publication, and data reuse.

Day two is practical and hands-on, focusing on how data management principles translate into everyday analytical practice in R, including writing cleaner, more efficient, and more reproducible code.

By the end of day one, you should be able to:

• reflect on what proportionate open and reproducible practice looks like
• identify which practices matter most in your own context
• recognise reproducibility as a form of risk reduction
• know where to go next for tools, guidance, and support.

By the end of day two, you should be able to implement basic data management and organisational techniques to write cleaner, more efficient, and more reproducible code in R.

Eligibility

The course is aimed at researchers working with administrative or routinely collected data, particularly those with limited or no formal training in data management or reproducible research practices. Delegates may register for either or both days. Day two assumes a basic working knowledge of R. The course will be capped at a maximum of 20 delegates.

The course will be delivered over Zoom. For day one, there are no special requirements. For day two, you will need a copy of R installed on your machine.

Event details

When: 

• Day one: Monday 23 March, 10:00 – 13:00
• Day two: Tuesday 24 March, 10:00 - 13:00

Where: Online 

Cost: Free

How to register: To reserve your space, please contact matthew.jay@ucl.ac.uk with your name and the days you would like to attend. We will follow up with pre-course information shortly. For any queries, please contact Liliane Broschart (l.broschart@ucl.ac.uk), Matthew Jay (matthew.jay@ucl.ac.uk) or Joana Cruz (joana.cruz@ucl.ac.uk).