Two Decades, Same Story? Insights and Future Directions in Long Tail Data Curation

This review paper explores the evolution of the "long tail" framework for research data and offers several provocations and recommendations based on that review. The "long tail" concept, originally borrowed from statistics to explain trends in digital consumer goods, refers to a vast array of smaller, heterogeneous data collections that cumulatively represent a substantial portion of scientific knowledge. However, these data collections are frequently overlooked due to inadequate data management practices and institutional support. The goal of this paper is threefold: a) to situate discussions of long tail data within the broader context of data curation paradigms, b) to bridge library and information science (LIS) with domain-specific contexts, and c) to draw insights and future directions for the field of long tail data curation that could enhance research and practice in information science. Ultimately, this literature review will contribute to a more comprehensive understanding of the long tail framework and help to reshape the agenda and future research and practice in long tail data curation.