Library Faculty/Staff Scholarship and Research

Permanent URI for this collectionhttp://hdl.handle.net/1903/11

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    Sharing and Collecting Latin American Publications in the Big Ten: Developing a Methodology for Consortial Data Analysis
    (2018-07) Gardinier, Lisa; Ostos, Manuel; Smith, Austin; Thompson, Hilary
    Inspired by the 2017 Big Ten Academic Alliance Collective Collection Conference, the presenters undertook a research study to better understand the consortium’s resource sharing needs for Spanish and Portuguese materials published in Latin America and to develop data-informed models for cooperative collection development of these publications. Using ILLiad custom request searches, Access queries, Python scripts, Google’s Language Detection Library, and WorldCat API, the presenters gathered and analyzed interlibrary loan and collections holdings data from the 15 members of the Big Ten Academic Alliance’s Library Initiatives. Given these libraries’ high volume of ILL requests and large collection sizes, it was imperative to employ various technologies to expedite analysis and reconcile data from different sources, making this project an excellent case study for exploring how to work with consortial data. In addition to presenting the study’s methodology and key findings, we hope this presentation encourages deeper analysis of consortial resource sharing, inspires greater cooperation in collecting for area studies, and helps libraries build distinctive collections to support consortial and national resource sharing.
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    Sharing and Collecting Latin American Publications in the Big Ten: Developing a Methodology for Consortial Data Analysis
    (2018-06) Gardinier, Lisa; Ostos, Manuel; Smith, Austin; Thompson, Hilary
    Inspired by the 2017 Big Ten Academic Alliance Collective Collection Conference, the presenters undertook a research study to better understand the consortium’s resource sharing needs for Spanish and Portuguese materials published in Latin America and to develop data-informed models for cooperative collection development of these publications. Using ILLiad custom request searches, Access queries, Python scripts, Google’s Language Detection Library, and WorldCat APIs, the presenters gathered and analyzed interlibrary loan and collections holdings data from the 15 members of the Big Ten Academic Alliance’s Library Initiatives. Given these libraries’ high volume of ILL requests and large collection sizes, it was imperative to employ various technologies to expedite analysis and reconcile data from different sources, making this project an excellent case study for exploring how to work with consortial data. In addition to presenting the study’s methodology and key findings, we hope that the poster encourages deeper analysis of consortial resource sharing, inspires greater cooperation in collecting for area studies, and helps libraries build distinctive collections to support consortial and national resource sharing.
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    Seeing Ares through ILLiad Glasses: New Approaches to Course Reserves from an ILL Practitioner
    (2016-11-09) Thompson, Hilary
    As part of a larger reorganization of the Resource Sharing & Access Services department at the University of Maryland Libraries in 2015, Course Reserves and Interlibrary Loan services and operations were consolidated into a single unit under the Interlibrary Loan supervisor. Thanks to the similarities between ILLiad and Ares, the new Resource Sharing & Reserves unit was able to leverage ILL staff members’ experience customizing Atlas Systems products and streamlining complex, high-volume workflows across multiple libraries to improve Course Reserves’ operational efficiency and user experience. This presentation will discuss key changes implemented over the past year, assess the effectiveness of the new model, and outline next steps for further improvement.