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Title:Shedding Light on the Dark Data in the Long Tail of Science
Author(s):Heidorn, P. Bryan
Subject(s):Data Curation
Data repositories
Long Tail
Abstract:One of the primary outputs of the scientific enterprise is data, but many institutions such as libraries that are charged with preserving and disseminating scholarly output have largely ignored this form of documentation of scholarly activity. This paper focuses on a particularly troublesome class of data, termed “dark data”. “Dark data” is not carefully indexed and stored so becomes nearly invisible to scientists and other potential users and therefore is more likely to remain underutilized and eventually lost. The article discusses how the concepts from long tail economics can be used to understand potential solutions for better curation of this data. The paper describes why this data is critical to scientific progress, some of the properties of this data, as well as some social and technical barriers to proper management of this class of data. Many potentially useful institutional, social and technical solutions are under development and are introduced in the last sections of the paper, but these solutions are largely unproven and require additional research and development.
Issue Date:2008-10
Publisher:The Johns Hopkins University Press
Citation Info:Library Trends 57(2) Fall 2008 (in press)
Publication Status:published or submitted for publication
Peer Reviewed:not peer reviewed
Rights Information:Attribution Non-commercial Creative Commons
Date Available in IDEALS:2008-10-19

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