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CLC number: G250.76; TP319

On-line Access: 2010-11-04

Received: 2010-09-14

Revision Accepted: 2010-10-10

Crosschecked: 2010-09-14

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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.11 P.872-881

http://doi.org/10.1631/jzus.C1001006


A methodology for measuring the preservation durability of digital formats


Author(s):  Chao Li, Xiao-hui Zheng, Xing Meng, Li Wang, Chun-xiao Xing

Affiliation(s):  Research Institute of Information Technology, Tsinghua University, Beijing 100084, China, Library of Tsinghua University, Tsinghua University, Beijing 100084, China

Corresponding email(s):   lichao00@tsinghua.org.cn

Key Words:  Digital preservation, Format obsolescence, Risk assessment model, Risk value


Chao Li, Xiao-hui Zheng, Xing Meng, Li Wang, Chun-xiao Xing. A methodology for measuring the preservation durability of digital formats[J]. Journal of Zhejiang University Science C, 2010, 11(11): 872-881.

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author="Chao Li, Xiao-hui Zheng, Xing Meng, Li Wang, Chun-xiao Xing",
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%DOI 10.1631/jzus.C1001006

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T1 - A methodology for measuring the preservation durability of digital formats
A1 - Chao Li
A1 - Xiao-hui Zheng
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A1 - Li Wang
A1 - Chun-xiao Xing
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1001006


Abstract: 
It is now widely recognized that appropriate measures are required for digital preservation to ensure that digital data can be accessed and used currently and in the future. Among all the risks of digital preservation, format obsolescence is one of the most important. There have been several projects or initiatives dealing with the measurement method of format obsolescence risk, but there has been no mechanism to quantify the preservation risk or durability of digital formats based on a self-improving assessment model, executed with the aid of computers. This paper deals with a methodology for measuring the preservation durability of digital formats, especially for their risk assessment. This method is based on a quantitative assessment model for format risk, and can shift the non-quantifiable knowledge or experiences of field experts to a machine identifiable and processible form, or ‘risk scores’. Results can be recognized and communicated by computers automatically and formally, which can assist in the automatic/semi-automatic risk management for digital preservation, sharing this quantified knowledge among communities. Because technologies are changing quickly, the quantitative assessment model for risks will not be a status quo situation. Thus, also presented is a method to fine tune the quantitative assessment model for risk of formats through a self-learning and self-improving style.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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