Data anonymisation

QAMyData is an easy-to-use, open source tool that provides a health check for numeric data. The tool uses automated methods to detect and report on some of the most common problems in survey or numeric data, such as missingness, duplication, outliers and direct identifiers.

The tool offers a number of configurable tests that have been categorised into four types: file, metadata, data integrity, and identifiers, which can be run on popular file formats, including SPSS, Stata, SAS and CSV. A standard config file has default settings for each test, such as a threshold for pass or fail on various tests (e.g. detect value label that are truncated, email addresses identified as a string, or undefined missing values) which can be easily adapted to meet the user’s own desired thresholds. The configuration feature allows the creation of a unique Data Quality Profile. The software creates a ‘data health check’ that details errors and issues as both a summary and detailed report, providing a location of the failed test. New tests can easily be added. Data depositors and publishers can act on the results and resubmit the file until a clean bill of health is produced.

YouTube Video: This introductory webinar is for anyone who is involved in the collection of data and is considering making (some of) their data available in accordance with funders’ requirements. This webinar aims to raise awareness about relevant key data management practices for sharing, specifically regarding data documentation, gaining consent, and data anonymisation. it provides a short theoretical introduction, including what FAIR means and how it is implemented, as well as practical illustrations drawing on a large-scale cross-national survey (the European Social Survey). It also provides some practical tips with respect to data archiving, in particular how to choose an appropriate archive or repository.

Training workshops, webinars and events on various data managemnet topics organised by the UK Data Service.

Slides of all events are made available on the past events pages. Recordings of webinars are made available on the UKDS YouTube channel. All can be used for training activities.

Key legal and ethical considerations in creating shareable data. This chapter clarifies the different legal requirements of the European Union Member States, and the impact of the General Data Protection Regulation (GDPR) on research data management. It shows how sharing personal data can often be accomplished by using a combination of obtaining informed consent, data anonymisation and regulating data access. The supporting role of ethical review in managing legal and ethical obligations is also highlighted in this chapter.

Focus on:

• legal and ethical obligations towards research participants and the different legal requirements of EU Member States
• how protecting data properly protects against violating laws and promises made to participants
• the General Data Protection Regulation and its relevance in research
• informed consent, anonymisation and access controls to facilitate creating shareable data
• relevant elements in a consent form
• anonymisation techniques for quantitative and qualitative data
• relevant DMP questions on these topics

This source includes interactive modules designed for users who want to get to grips with key aspects of survey, longitudinal and aggregate data as well as tools that can be used to assess and improve data quality. 

Modules can be conducted in your own time and you are able to dip in and out when needed. The modules give an introduction to key aspects of the data using short instructional videos, interactive quizzes and activities using open access software where possible. Tools include guides, documentation and exercises.

Online data management guidance and resources for researchers, developed by the UK Data Service. This resource provides best practice guidance and advice, including examples, exercises, tools and templates. The focus is on the social sciences and research with human participants. Particular areas covered are:

• Data management planning
• Legal and ethical aspects of managing and sharing data
• IP Rights
• Documenting data
• Formatting data
• Storing data

The Data Management Expert Guide is designed by European experts from the CESSDA Training Working Group to help social science researchers make their research data Findable, Accessible, Interoperable and Reusable (FAIR).

The guide is written for social science researchers who are in an early stage of practising research data management. With this guide, CESSDA wants to contribute to professionalism in data management and increase the value of research data.

The guide leads through the research data lifecycle from planning, organising, documenting, processing, storing and protecting data to sharing and publishing them. Taking the whole roundtrip will take approximately 15 hours.

Particular specialties of the guide is a focus on European diversity (for example in data protection legislation, research ethics, research funder DMP requirements, etc), developing a Data Management Plan as you progress through the guide, and topical expert tips.