Issue no.3

ISSN: 2328-0972
November 2014

Articles

In 2008, the University of Minnesota Archives developed a low-cost, in-house solution for routine mass digitization of university publications, reports, and records. The strategies offered in this paper highlight a practical program for the mass digitization of organizational archival records using a rapid capture process that is replicable regardless of the size or resources of the repository. It will review the establishment of the rapid capture workflow at the University of Minnesota Archives; provide details on how it functions, including equipment information, scanner settings, and workflow procedures; explain the selection process for scanning; describe how it has helped to create inreach opportunities; and finally, examine how it has changed not only daily operations, but the perspective on what it means to provide broad access to the collections.

XML has long been an important tool for archivists. The addition of XQuery provides a simple and easy-to-learn tool to extract, transform, and manipulate the large amounts of XML data that archival repositories have committed resources to develop and maintain – particularly EAD finding aids. XQuery allows archivists to make use of that data. Furthermore, using XQuery to query EAD finding aids, rather than merely reformat them with XSLT, forces archivists to look at finding aids as data. This will provide better knowledge of how EAD may be used and further understanding of how finding aids may be better encoded. This article provides a simple how-to guide to get archivists to start experimenting with XQuery.

This article illustrates how archival finding aids or other documents in any common word processing file format can be mass converted to web friendly PDF and HTML formats with free software so they can be made available on the web. Files are initially uploaded to Google Drive, then converted and downloaded in either PDF or HTML format. For HTML files code is then edited in Notepad++ if necessary. The intended audience for this article is smaller institutions with fewer technological resources to devote to creating full EAD finding aids or exporting information to a database, but who nevertheless would like to place large numbers of finding aids or other text-based documents online.

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