ABSTRACT:

The General Data Protection Regulation (GDPR) grants all natural persons within the EU the right to an electronic copy of their personal data as collected by data controllers upon request. All major data controllers comply with this right by providing their clients with a so-called `Data Download Package' (DDP). Recently, a workflow was introduced that allows researchers to analyse the digital traces found in these DDPs while preserving the privacy of the research participant. In this presentation, I will discuss this workflow and its challenges by means of a so-called ‘total error framework’. In addition, I will introduce a proof-of-concept of the software that allows an essential local processing step to take place within this workflow. At last, I will illustrate the use of the workflow and software by means of a practical example.

BIO:

Laura Boeschoten is an Assistant Professor at the Department of Methodology and Statistics at Utrecht University. For her PhD research she developed methodology that simultaneously estimates and corrects for measurement error in combined survey-register datasets, a combined project at Tilburg University in Statistics Netherlands. During her PhD, she worked for collaborative projects with the Italian Statistical Institute (ISTAT), New York University (NYU).

She aims to expand the field of measurement error estimation and correction in such a way that these methodologies can also be applied to other data types, particularly to digital trace data. As a first step in this process, she recently developed software that allows for a privacy preserving analysis of digital traces.

Please email naomi.snowball@anu.edu.au for the zoom link