Diversity in data: Lessons from interdisciplinary practices

Interdisciplinary research has seen a substantial growth in the past several decades, and data management plays a crucial role in this trend. New tools and sources of data drive interdisciplinarity and collaborations, and, in turn, interdisciplinary research produces complex, heterogeneous datasets that require different forms of data management and curation. How do interdisciplinary project members negotiate their work around diverse datasets? What role do ethics play in their data practices? How do interdisciplinary teams approach privacy and confidentiality as they collect, store, and organize their heterogeneous datasets? Previous research on interdisciplinary research practices often addresses issues of team dynamics rather than data management and curation. In this presentation we will share results from our study examining several interdisciplinary projects and their complex data practices.

Through interviews, observations, and document analysis we have gathered a rich dataset about interdisciplinary data management and curation, and the role of universities in supporting such projects. We will illustrate how interdisciplinary projects, primarily in the social sciences and humanities, collaborate internally and externally and use tools and resources to share, organize, and curate their data. In particular, we will present a use case exhibiting the challenges and nuances of working with vulnerable or historically underrepresented populations. Our findings show that individual disciplinary backgrounds, particularly of the project leaders, affect how projects approach their data and its sensitivity and how they decide to grapple (or not) with issues of representation or privacy. To engage the audience in the further discussion, we will conclude our presentation with insights on data documentation, software interoperability, and collaborative dynamics in interdisciplinary projects.