Assessing Data Quality and Disclosure Risk in Numeric Data: a hands-on workshop
Summary
This hands-on workshop will introduce the principles of data quality, disclosure risk assessment, and tools available that can be used to undertake a review of numeric data. The session is led by the UK Data Service.
Description
Data assessment is a key activity in the research process - researchers often need to quickly analyse datasets they receive to verify that it contains sufficient information to perform their analysis and excludes personal data. Similarly, they must assess the quality of their own data when preparing it for publication, by ensuring it has been sufficiently de-identified and contains information that enables reuse.
Data checks are essential for complying with ethical and legal requirements (such as GDPR), as well as addressing funder and journal objectives for enhanced transparency and replication. However, they are time consuming if performed in a manual and un-coordinated manner.
On this hands-on training, you will learn about the key elements of data quality and disclosure risk, including: file checks, data and metadata checks, direct and indirect identifiers, and be introduced to two tools that can be used to perform a 'health check' on your data.
- QAMyData is an open source tool developed by the UK Data Service that can be used to automatically assess and report on elements of quality, such as missingness, labelling, duplication, formats, outliers and direct identifiers.
- sdcMicro is a practical R package for checking disclosure risk through examining combinations of key variables.
Practical demonstrations and hands-on exercises will be used throughout the afternoon and we will finish with a session on how to download the software yourself so that you can use them after the workshop, or integrate them into routine data cleaning and processing pipelines when creating, using, reviewing or publishing data.
Requirements
Attendees wishing to participate in practical activities are encouraged to bring a laptop installed with R (https://www.r-project.org/) and RStudio https://www.rstudio.com/products/RStudio/).
To register your attendance please RSVP to Gareth.Knight@lshtm.ac.uk
Admission
Contact