Digital trace data collection through data donation
- URL: http://arxiv.org/abs/2011.09851v1
- Date: Fri, 13 Nov 2020 11:19:25 GMT
- Title: Digital trace data collection through data donation
- Authors: Laura Boeschoten and Jef Ausloos and Judith Moeller and Theo Araujo
and Daniel L. Oberski
- Abstract summary: Article 15 of the EU's General Data Protection Regulation: 2018 mandates individuals have electronic access to their personal data.
All major digital platforms now comply with law by users with "data download packages" (DDPs)
Through all data collected by public and private entities, citizens' digital life can be obtained and analyzed to answer social-scientific questions.
We provide a blueprint for digital trace data collection using DDPs, and devise a "total error framework" for such projects.
- Score: 0.4499833362998487
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: A potentially powerful method of social-scientific data collection and
investigation has been created by an unexpected institution: the law. Article
15 of the EU's 2018 General Data Protection Regulation (GDPR) mandates that
individuals have electronic access to a copy of their personal data, and all
major digital platforms now comply with this law by providing users with "data
download packages" (DDPs). Through voluntary donation of DDPs, all data
collected by public and private entities during the course of citizens' digital
life can be obtained and analyzed to answer social-scientific questions - with
consent. Thus, consented DDPs open the way for vast new research opportunities.
However, while this entirely new method of data collection will undoubtedly
gain popularity in the coming years, it also comes with its own questions of
representativeness and measurement quality, which are often evaluated
systematically by means of an error framework. Therefore, in this paper we
provide a blueprint for digital trace data collection using DDPs, and devise a
"total error framework" for such projects. Our error framework for digital
trace data collection through data donation is intended to facilitate high
quality social-scientific investigations using DDPs while critically reflecting
its unique methodological challenges and sources of error. In addition, we
provide a quality control checklist to guide researchers in leveraging the vast
opportunities afforded by this new mode of investigation.
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