Assessing Data Quality and Disclosure Risk in Numeric Data (join a waiting list)

Course Code

HUB-05-18/19-P-R

Organised by

NCRM, University of Southampton

Presenter

Louise Corti, Sharon Bolton, Cristina Magder, Anca Vlad and Myles Offord

Date

20/02/2019

Venue

St Clements Building, London School of Econonics, St Clements Lane, London

Map

View in Google Maps  (WC2A 2AB)

Contact

Jacqui Thorp
Training and Capacity Building Co-ordinator
National Centre for Research Methods
Tel: 02380594069
Email: jmh6@soton.ac.uk

Description

In this hands-on day course you will learn about the principles of, and tools for, assessing data quality and reviewing disclosure risk in numeric data sources. Data assessment is extremely useful whether it is for wishing to create a high quality data for publishing, thereby supporting  the transparency and replication agenda (e.g. to meet funder or journal policy), or simply to check unknown data that has been accessed for reuse. The requirements of the GDPR when processing and de-identifying data benefit from quick examination, using tools where possible.

The course will introduce the key elements of data quality and disclosure risk, including: file checks, data and metadata checks, and direct and indirect identifiers. The day makes use of two tools to undertake review. The first is QAMyData that automatically assesses elements of quality, such as missingness, duplication, outliers and direct identifiers. A user can specify and set thresholds in the QAMYData tool, to indicate what one is prepared to accept (i.e. no missing data or data must be fully labelled). Issues are identified in both a summary and detailed report. The second tool is R sdcMicro, a practical tool for checking disclosure risk through examining combinations of key variables.

Practical demonstrations and hands-on exercises will be used throughout. The course will be held in a lab where the software will be mounted. However, these software are easily downloaded to a laptop and be quickly used after the workshop and can be integrated into data cleaning and processing pipelines for data creators, users, reviewers and publishers.

The course covers:

  • Short presentations on the principles and practicalities of assessing data quality and undertaking disclosure review in numeric data;
  • Practical demonstrations and hands-on exercises for assessing data quality and undertaking disclosure review in numeric data;
  • A short session surgery on installing the tools for onward use.

By the end of the course participants will:

  • Appreciate the principles and practicalities involved in assessing data quality and undertaking disclosure review in numeric data;
  • Gain hand-on experience with using two piece of software: QAMyData, for assessing data and metadata quality, and R sdcMicro for disclosure review in numeric data;
  • Know how to install QAMyData and R sdcMicro on their own computers.

 

Target Audience

Academics, lecturers, researchers and data publishers from all sectors who are interested in the practical elements of assessing numeric data for quality and disclosure risk.

Pre-requisites

Some knowledge about the creation and QA of survey or numeric data are expected, as is familiarity with some kind of statistics software tools e.g. SPSS, STATA or R.

 

Level

Intermediate (some prior knowledge)

Cost

The fee per teaching day is:

• £30 per day for UK/EU registered students.
• £60 per day for staff at UK/EU academic institutions, UK/EU Research Councils researchers, UK/EU public sector staff and staff at UK/EU registered charity organisations and recognised UK/EU research institutions.
• £220 per day for all other participants.

All fees include event materials, lunch, morning and afternoon tea. They do not include travel and accommodation costs.

Full refunds are available two weeks prior to the course, NO refunds are available after this date.

Website and registration

Region

Greater London

Keywords

Qualitative Data Handling and Data Analysis, Disclosure review , Privacy Impact Assessment , sdcMicro , Open source tools , Transparency , Replication , , , , Data Publishing

Related publications and presentations

Qualitative Data Handling and Data Analysis

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