What question did this study set out to answer?

To explore intrinsic data quality and its measurement dimensions in various types of research data.

March 21, 2026Open Access

Intrinsic Data Quality: Measurement Dimension Slide deck

Key Points

To explore intrinsic data quality and its measurement dimensions in various types of research data.
Overview of intrinsic data quality concepts
Identification of common data quality pitfalls
Examination of measurement dimensions in popular data quality frameworks
Classification of research data into survey, digital behavioral, and linked data
Clarified the impact of data quality on research outcomes
Outlined different types of data and their associated quality issues
Highlighted the significance of frameworks in assessing data quality

Abstract

This presentation provides an introduction to intrinsic data quality, covering some common data quality pitfalls and explaining how data quality affects research outcomes. It also gives an introduction to measurement dimensions of popular data quality frameworks, distinguishing between three types of research data: survey data, digital behavioral data, and linked data. This presentation is the second part of a set of presentations on the topic of "Terms, Concepts & Frameworks of Data Quality". Presentation available after free registration: https://elearning.gesis.org/course/section.php?id=1202

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