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Volume: 7 | Article ID: art00029
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Visualization for Archival Appraisal of Large Digital Collections
Weijia Xu
Maria Esteva
Suyog Jain Dott
  DOI :  10.2352/issn.2168-3204.2010.7.1.art00029  Published Online :  January 2010
Abstract

Our research examines data-driven visualization methods for archival purposes. Using data extracted from a large and heterogeneous digital collection, we created an information visualization that uses RDBMS and treemap to enable archival analysis. Different views present the collection's structure and properties at different levels of aggregation and abstraction, transforming 1,000,000 data points into information that enables observation and decision-making.

Journal Title : Archiving Conference
Publisher Name : Society of Imaging Science and Technology
Publisher Location : 7003 Kilworth Lane, Springfield, VA 22151, USA
Subject Areas :
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 DOI 10.2352/issn.2168-3204.2010.7.1.art00029
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Weijia Xu, Maria Esteva, Suyog Jain Dott, "Visualization for Archival Appraisal of Large Digital Collections"  in Proc. IS&T Archiving 2010,  2010,  pp 157 - 162,  https://doi.org/10.2352/issn.2168-3204.2010.7.1.art00029

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Copyright © Society for Imaging Science and Technology 2010
72010361
Archiving Conference
archiving
2161-8798
Society of Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151, USA
2161-8798(20100101)2010:1L.157;1-
ac_v2010n1/splitsection29.xml
/ist/ac/2010/00002010/00000001/art00029
Articles
Visualization for Archival Appraisal of Large Digital Collections
XuWeijia
EstevaMaria
DottSuyog Jain
01012010
2010
1
157
162
2010
Our research examines data-driven visualization methods for archival purposes. Using data extracted from a large and heterogeneous digital collection, we created an information visualization that uses RDBMS and treemap to enable archival analysis. Different views present the collection's structure and properties at different levels of aggregation and abstraction, transforming 1,000,000 data points into information that enables observation and decision-making.