Fostering Research Data Management in Collaborative Research Contexts: Lessons learnt from an ‘Embedded’ Evaluation on designing a ‘Data Story’

Abstract

Research Data Management (RDM) practices – spanning the curation, storage, sharing, and reusability of research data – are foundational to the Open Science (OS) agenda. Because of that, many and various funding institutions are increasingly demanding active engagement of researchers in them. Nevertheless, recent studies suggest that RDM practices are not yet properly integrated into daily research workflows, nor supported by any tools researchers typically use. In this paper, we introduce evaluation results of a technological aid for implementing a design concept called ‘Data Story’, drawing on ideas from digital and data storytelling. This concept has been devised to facilitate the appropriation of RDM practices by researchers working mainly with qualitative data in their daily workflows. It integrates traditional data curation approaches with a more narrative, contextual, and collaborative organizational layer that can be thought of as a ‘story’. Our findings come from a long-term ‘embedded’ evaluation of the concept and show: (1) the potential benefits of engaging with a Data Story for RDM; (2) Data Curation issues and learning opportunities; and (3) a broader set of issues and concerns that remain unaddressed in the current state of play. Our contribution, based on lessons learnt, is to provide a new design approach for RDM and for new collaborative research data practices, one grounded in narrative structures, capable to negotiate between top-down policies and bottom-up practices, which supports ‘reflective’ learning opportunities - with and about data - of many kinds.

Types of domain and task‐solving information in media scholars' data interaction

“…This could be done by designing tools that support exploration, discovery, and insights during the data interaction. For example, Mosconi et al (2023) designed a data story tool that supported not only data management but also analytical insights, conversations, and peer learning. Second, the various task‐supporting documents created during data interaction could be important sources for sharing information to others—not just about how the research was conducted—but also about the intentions and rationales behind it, which may be important information to those who consider reusing the data for their own research purposes (Yakel et al, 2022).…”