Leveraging Python to improve ebook metadata selection, ingest, and management
Libraries face many challenges in managing descriptive metadata for ebooks, including quality control, completeness of coverage, and ongoing management. The recent emergence of library management systems that automatically provide descriptive metadata for e-resources activated in system knowledge ba...
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doaj-69bb0d6356144ed2b8751b01995a439f2020-11-25T03:53:22ZengCode4LibCode4Lib Journal1940-57582017-10-013812828Leveraging Python to improve ebook metadata selection, ingest, and managementKelly ThompsonStacie TraillLibraries face many challenges in managing descriptive metadata for ebooks, including quality control, completeness of coverage, and ongoing management. The recent emergence of library management systems that automatically provide descriptive metadata for e-resources activated in system knowledge bases means that ebook management models are moving toward both greater efficiency and more complex implementation and maintenance choices. Automated and data-driven processes for ebook management have always been desirable, but in the current environment, they become necessary. In addition to initial selection of a record source, automation can be applied to quality control processes and ongoing maintenance in order to keep manual, eyes-on work to a minimum while providing the best possible discovery and access. In this article, we describe how we are using Python scripts to address these challenges.http://journal.code4lib.org/articles/12828 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kelly Thompson Stacie Traill |
spellingShingle |
Kelly Thompson Stacie Traill Leveraging Python to improve ebook metadata selection, ingest, and management Code4Lib Journal |
author_facet |
Kelly Thompson Stacie Traill |
author_sort |
Kelly Thompson |
title |
Leveraging Python to improve ebook metadata selection, ingest, and management |
title_short |
Leveraging Python to improve ebook metadata selection, ingest, and management |
title_full |
Leveraging Python to improve ebook metadata selection, ingest, and management |
title_fullStr |
Leveraging Python to improve ebook metadata selection, ingest, and management |
title_full_unstemmed |
Leveraging Python to improve ebook metadata selection, ingest, and management |
title_sort |
leveraging python to improve ebook metadata selection, ingest, and management |
publisher |
Code4Lib |
series |
Code4Lib Journal |
issn |
1940-5758 |
publishDate |
2017-10-01 |
description |
Libraries face many challenges in managing descriptive metadata for ebooks, including quality control, completeness of coverage, and ongoing management. The recent emergence of library management systems that automatically provide descriptive metadata for e-resources activated in system knowledge bases means that ebook management models are moving toward both greater efficiency and more complex implementation and maintenance choices. Automated and data-driven processes for ebook management have always been desirable, but in the current environment, they become necessary. In addition to initial selection of a record source, automation can be applied to quality control processes and ongoing maintenance in order to keep manual, eyes-on work to a minimum while providing the best possible discovery and access. In this article, we describe how we are using Python scripts to address these challenges. |
url |
http://journal.code4lib.org/articles/12828 |
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