The Promise and Practice of Sharing Qualitative Data in Communication Research: Insights from the Qualitative Data Repository
As open science ideas gain traction in communication and media studies, qualitative researchers face unique challenges and opportunities in adopting transparent and reproducible practices. This article contributes to the growing conversation on open research infrastructures by introducing the Qualitative Data Repository (QDR) as a domain-specific solution for qualitative and multi-method data sharing. QDR is particularly well-equipped to manage data derived from human participants or existing media materials, both of which are widely used in this field. We explore how QDR’s infrastructure, services, and ethical frameworks can be adapted to the needs of communication scholars. First, we briefly outline the benefits of qualitative data sharing—including increased transparency, methodological rigor, and pedagogical value—while acknowledging possible barriers such as ethical concerns, time constraints, and disciplinary histories. We then review practical developments that have taken place over the last five years by scholars practicing some of the principles for trustworthy qualitative communication research laid out by Humphreys et al. (2021). Using examples from a wide variety of projects where QDR has already facilitated data publication and annotations for transparent inquiry, we illustrate how similar practices can be adopted systematically in communication research. We also highlight QDR’s support for researchers throughout the data lifecycle, from planning and consent to curation and controlled access. This article aims to demystify qualitative data sharing and encourage broader adoption among communication and media studies scholars by showcasing QDR’s model and its alignment with findable, accessible, interoperable, reusable principles. We argue that embracing more open and transparent research practices not only enhances the quality and visibility of individual projects but also fosters a more inclusive and collaborative scholarly community.
Authors
- Lee Humphreys
- Dessislava Kirilova
Publication Details
- Journal
- Cogitatio (Cogitatio)
- Published
- 2026-10-01
- DOI
- https://doi.org/10.17645/mac.12354
- Primary Topic
- Data Analysis and Archiving
- Type
- article
- Field-Weighted Citation Impact
- 0.00