Jan 24, 2021

DAPPER – Data Analysis with Privacy Protection for Epidemiological Research


DAPPER stands for Data Analysis with Privacy Protection for Epidemiological Research. Firstly, it will organise a workshop focusing on tools and approaches allowing sensitive data to be shared and analysed without being physically transferred between researchers. The effective exploitation of what are often called Big Data is increasingly important. They provide the “evidence” in “evidence-based health care” and underpin scientific progress in many domains including social/economic policy. Typically, an optimal (efficient and flexible) analysis involves working directly with “microdata”, i.e. the detailed data relating to each individual in the dataset. But there are many ethico-legal and other governance restrictions on physically sharing microdata. Researchers or institutions may have an extensive intellectual property investment in complex microdata and although keen for other researchers to analyse their data they may not wish to give them a physical copy. These restrictions can discourage the use of optimum approaches to analysing pivotal data and slow scientific progress.

Data science groups across the world are exploring privacy-protected approaches to analysing microdata without having to physically share the data. Two innovative approaches, DataSHIELD and VIPAR, are being developed by WUN universities. DAPPER will run a WUN-hosted international workshop addressing methods across the field. Practical sessions will be of central importance allowing potential users to explore different approaches in action by running analyses themselves. The workshop will be held in Bristol in August 2016 allowing participants to attend the 2016 International Population Data Linkage Network Conference (August 24-26) in Wales.

The workshop will provide the foundation for an integrative white paper summarising the current status of the field. Together, the workshop and white paper will map out key opportunities and challenges, and help potential users, developers and other stakeholders (e.g. funders/journals) to recognise the strengths and weaknesses of different approaches.

Across WUN, DAPPER will encourage methodological work in this field and better informed application of existing methods.