Exploring the Long Tail of Astronomy: A Mixed-Methods Approach to Searching for Dark Data

Abstract

As research datasets and analyses grow in complexity, data that could be valuable to other researchers and to support the integrity of published work remain uncurated across disciplines. These data are especially concentrated in the “Long Tail” of funded research where curation resources and related expertise are often inaccessible. In the domain of astronomy - which relies heavily on sophisticated instrumentation - it is undisputed that “dark” uncurated data exist, along with data at risk of becoming dark in the future. However, the scope of the problem remains uncertain. The dissertation project described here implements a mixed-methods research approach to characterize the Long Tail in astronomy as well as the properties of uncurated and at-risk astronomical data, and to develop methods for locating potentially-useful data to be targeted for curation through indicators in the scholarly literature. This project aims to enhance our understanding of the nature and prevalence of astronomical dark data and characterize astronomy’s Long Tail by: conducting interviews with experts; mapping the decision-making protocols used by astronomers while searching the astronomical literature for references to underlying data; and conducting a survey of authors of journal publications with a questionnaire about the data associated with their papers. The project aims to deepen scholarly insight into domain-specific astronomy data practices, overall addressing epistemological claims that enhanced data access and open science result in scientific knowledge and producing a characterization and theory of the distribution and accessibility of dark and at-risk data in astronomy.