Regardless of the specific methods used in their research, by the end of the PhD all NWSSDTP-funded students are expected to be able to demonstrate competency in the skills required to manage data effectively, whether they are using existing data or creating new data (including digital data capture). This includes developing an appreciation of intellectual, practical and ethical issues:

• Using Open Science principles and practices from the beginning of a project to enhance reproducibility; Checking, cleaning, and preparing materials for analysis using reproducible processing pipelines;
• Data quality assurance measures including data cleaning, fixing inconsistencies and removal of coding errors;
• Manipulating and coding data;
• Ability to record and represent different modes of data (such as textual, aural and visual) using a range of data visualisation techniques;
• Secure data storage;
• Preparing materials/data/code for dissemination or deposit in a suitable repository for wider use (including the relevant analysis code and /or documentation to permit reproducibility);
• Archiving;
• Safe methods of disposing of data and General Data Protection Regulation (GDPR) Students must also be made aware of the UKRI Open Access Policy and its requirements.

NWSSDTP Training Catalogue Under Development