June 10-13, 2019 | Hamburg, Germany
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
P1E: Measuring use and reuse
Reuse and use: new definitions for digital library assessment
1University of Illinois at Urbana-Champaign, United States of America; 2University of Houston Libraries; 3Loyola University New Orleans; 4Virtual Library of Virginia; 5University of Southern California; 6Utah State University
This presentation explores the complexities of measuring the impact of use vs. reuse among cultural heritage and knowledge organizations (including but not limited to museums, libraries, archives, data repositories, and historical societies). It will provide an overview of the project team’s evolving definitions for use and reuse, informed by their work with the Measuring Reuse project. These definitions help delineate the differences between reuse and use, thus setting the stage to help information professionals determine which use cases should be considered use or reuse and developing more detailed and relevant assessments of the impact of digital collections. The speakers will apply the new definitions to specific use cases to show their utility and value and suggest how these efforts will lead to more informed assessment methods of digital library materials.
The BitViews project: a new method for aggregating online usage data, a new route to universal Open Access.
1University of St Andrews, United Kingdom; 2University of New South Wales and University of Sydney, Australia
Academics, librarians, university administrators, research funders all agree that having aggregated, worldwide, reliable, and validated data on online usage of scientific, scholarly, and medical peer-reviewed outputs would be highly desirable. Current initiatives to collate views data across publishers and institutional repositories, validating the data using the COUNTER protocol, are unlike to succeed because they are predicated on the concept of central clearing-house which is expensive to maintain and not scalable. The BitViews project uses open-source blockchain technology (a distributed publicly-accessible ledger protecting the privacy of viewing data) and thus provides a low-cost solution which bypasses the need for a central clearing house. As soon as online usage data are aggregated on a worldwide basis, they provide the raw material for devising discipline-specific non-citation impact metrics. Authors of scientific, scholarly, and medical peer-reviewed outputs will have a strong personal incentive to maximise the visibility (as opposed to the citability) of their work and therefore will voluntarily want to deposit their postprints on open access repositories. Librarians, university administrators, and academics ought to work together to make online usage data open data and realise that BitViews can turn open data into open access for all (dovetailing with Plan S).
Analyzing Aggregate IR Use Data from RAMP
1Montana State University, United States of America; 2University of Alberta, Canada; 3University of New Mexico, United States of America
Data collected from 50 institutional repositories (IR) on various platforms and from around the world will be analyzed for this presentation to demonstrate aggregate IR performance, use, and the visibility of content. The Repository Analytics & Metrics Portal (RAMP) is a free web service developed in 2017 with funding from the Institute of Museum and Library Services. The dataset collected by RAMP currently exceeds 300 million rows and it is the only open aggregate data available to evaluate the visibility and use of IR content, diagnose deficiencies with performance, align content with user needs, and optimize metadata for maximum click-through ratios, among myriad other potential uses. This presentation will address several potential research questions that could help improve IR performance and demonstrate the IR value proposition. Methods for extending the RAMP dataset’s analytic potential through augmentation with complementary, publicly available datasets will be described. The presentation will encourage audience members to register their own repositories with RAMP and/or to consider additional ways to analyze the dataset.
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