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August 14, 2017 by Gary Price

New Journal Article: “Persistence Statements: Describing Digital Stickiness”

August 14, 2017 by Gary Price

The following article was published today by Data Science Journal.
Title
Persistence Statements: Describing Digital Stickiness
Authors
John Kunze
University of California
Scout Calvert
Michigan State University
Jeremy D. DeBarry
University of Georgia
Matthew Hanlon
Texas Advanced Computing Center
Greg Janée
University of California
Sandra Sweat
Athena Health
Source
Data Science Journal. 16, p.39
doi:10.5334/dsj-2017-039
Abstract

In this paper we present a draft vocabulary for making “persistence statements.” These are simple tools for pragmatically addressing the concern that anyone feels upon experiencing a broken web link. Scholars increasingly use scientific and cultural assets in digital form, but choosing which among many objects to cite for the long term can be difficult. There are few well-defined terms to describe the various kinds and qualities of persistence that object repositories and identifier resolvers do or don’t provide. Given an object’s identifier, one should be able to query a provider to retrieve human- and machine-readable information to help judge the level of service to expect and help gauge whether the identifier is durable enough, as a sort of long-term bet, to include in a citation. The vocabulary should enable providers to articulate persistence policies and set user expectations.

Direct to Full Text Article

Filed under: Data Files, Journal Articles, News, Open Access

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About Gary Price

Gary Price (gprice@gmail.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.

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