Shedding light on the dark data in the long tail of science

Research output: Contribution to journalArticlepeer-review

224 Scopus citations

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 it 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.

Original languageEnglish (US)
Pages (from-to)280-299
Number of pages20
JournalLibrary Trends
Volume57
Issue number2
StatePublished - 2008
Externally publishedYes

ASJC Scopus subject areas

  • Library and Information Sciences

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