Improving Access to Standards

Abstract

As liaison librarian to several departments at UNLV, she teaches information literacy for many students, provides reference assistance to the campus and community, and maintains the collection in assigned subject areas. Her research interests include information literacy instruction and assessment, the notion of threshold concepts, the effect a student's emotional state has on their learning, and improving access to technical literature.

Desperately Seeking Standards: Using Text Processing to Save Your Time

“…We analyzed the method described by Wainscott and Zwiercan [7] and their unpublished data to get more detail and the approximate time spent on each step. The data set included four years of ILL requests, a total of 38,230 records, or requested items.…”

“…All items determined to be standards were then reviewed to determine if the request was fulfilled by ILL staff by any means. [7] To replace the Scan step, Author 1 first developed a regular expression, using Python in Jupyter Notebooks (code, documentation, and de-identified dataset can be found on Author 1's GitHub: https://github.com/hburns2/desperately-seeking-standards). Regular expressions (or regex), used for text processing and querying, identify patterns within written text.…”

“…Interlibrary loan (ILL) data have been used by librarians to provide useful insights into what materials patrons are seeking and in which subject areas a library's collections may need more depth [4]. ILL request data has also been used in combination with circulation, electronic resource use counts, and turnaway data (counts of user attempts to access electronic resources that result in a failure to access fulltext) to inform collection development decisions, primarily for monographs and journal articles [5], [6] but also for other formats such as standard documents [7]. ILL data has additionally been used to gauge the value of an improved discovery system (federated search tool used by libraries to provide patrons a single search box that operates simultaneously across multiple collections and databases) and link resolvers (software tool that seeks full-text access to items across multiple collections) to direct patrons to library-provided items [8], [9].…”

“…We sought to develop a text processing method to detect mentions of engineering standards and other standards documents in interlibrary loan datasets, as well as in large blocks of text, such as full-texts of theses and dissertations or within other publications. Using a portion of the same dataset analyzed by Wainscott and Zweircan [7], we applied a text processing method to identify probable requests for standards documents and compared our results to theirs. We also tested this method on five full-text dissertation documents.…”

“…The Preparation steps used by Wainscott and Zwiercan [7] were replicated and timed, taking a total of 15 minutes. Unpublished calendar data from Wainscott (Author 2 of the present analysis) were then used to estimate the time spent on the initial manual Scan portion of their process, shown in Table 1.…”