Quality Assurance in Digital Trace Data gathered through Data Donations: Frameworks, Tools, and Best Practices |
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| Coordinator 1 | Mr Yannik Peters (GESIS - Leibniz Institute for the Social Sciences) |
| Coordinator 2 | Mrs Fiona Draxler (University of Mannheim) |
| Coordinator 3 | Mrs Laura Young (University of Mannheim) |
| Coordinator 4 | Mrs Jessica Daikeler (GESIS - Leibniz Institute for the Social Sciences) |
In the evolving landscape of survey research, new data sources, such as digital trace data (e.g., online interaction, social media and browsing behavior data), have garnered significant attention. While the value of combining survey data and digital behavioral data in the form of data donation offers great potential for social science research, their practical implementation from a survey research perspective presents unique challenges. Those challenges particularly concern data quality and reliability.
This session will delve into the critical aspects of quality assurance in the context of collecting digital trace data through data donations. We will explore comprehensive frameworks, state-of-the-art tools, and best practices tailored to ensure the integrity and usability of these data sources.
Key topics will include:
1. Frameworks for Quality Assurance: An overview of frameworks designed to evaluate the quality of digital trace data through data donations, including criteria for assessing reliability, validity, and representativeness.
2. Tools and Platforms for Data Validation: A discussion on tools, technologies, and platforms (e.g., the KODAQS toolbox) for validating the quality of digital trace data collected through data donations.
3. Best Practices and Case Studies: Case studies on data donation for collecting and processing online interaction data, focusing on assessing data quality and providing examples of how to measure and improve it. Real-world case studies will illustrate successful integration of these data types into survey research, highlighting challenges and solutions.
4. Didactics of Data Quality Issues: Strategies for teaching data quality assurance for digital trace data through data donations. This segment will focus on educational approaches.
This session aims to foster a deeper understanding of the methodological challenges and practical solutions in assuring the quality of data donations and digital trace data in survey research.