Abstract
Quantitative data, the foundation of scientific research, have been in the foreground of discussions about data creation, curation, and publication pipelines. However, data for humanistic and social scientific inquiries take many forms, including physical and ephemeral primary resources (books, objects, performances, interactions); qualitative, free-form observations; as well as quantitative, structured data and metadata. At the Vanderbilt University Jean and Alexander Heard Library, we started the Tiny Data Working Group (TDWG) in 2016 to tackle some of the humanistic research data creation and curation issues in a constructive, collaborative, and interdisciplinary format. The present paper considers what it means to be FAIR with humanities data, as well as how to build a community of data-literate humanists, based on our experiences with the TDWG.
Highlights
As data curators strive to make data management an integral component of the research lifecycle, it is necessary to delve into discipline-specific ways of defining and interacting with data
Contemporary principles of good data management and stewardship derive primarily from scientific research workflows, as reflected in the science-oriented language and examples presented in the recent statement of the FAIR principles (Wilkinson et al, 2016)
The growing infrastructure to sustain FAIR data, including workflow management platforms such as the Open Science Framework (OSF) and data repositories such as Dataverse, Figshare, and Zenodo, is being shaped by the needs of scientists working in collaborative laboratories on quantitative data
Summary
As data curators strive to make data management an integral component of the research lifecycle, it is necessary to delve into discipline-specific ways of defining and interacting with data. We focus on the humanities (and social sciences) by guiding participants towards nuanced, data-driven methods for answering humanistic research questions; by demonstrating and facilitating sound data collection and management practices; and by identifying appropriate places to deposit and access data from completed projects. The authors had already started work on defining ‘Tiny Data’ and the relationship between it and computational approaches to humanistic research; when the graduate students expressed interested in experimenting with their research topics through the controlled application of data management and visualization tools, the first iteration of the TDWG was convened. The deliverables from the first semester of the TDWG included the completion/initiation of two research projects, and something less tangible: the formation of a cohort of humanities graduate students with a heightened understanding of the strengths and pitfalls of digital data-modelling tools and a new perception of the role the Library could play in the formative stages of their research. A few of the things we have learned over the past year are outlined below
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