Hybrid linked data approaches in traditional discovery environments using Share-VDE linked data
Penn collection
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discovery
semi-automated indexing
Annif
machine learning
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Abstract
Hybrid linked data approaches for traditional discovery environments improve discovery in contemporary library systems using Share-VDE (SVDE) linked data. Hybrid linked data environments include “traditional” data structures alongside linked data systems and processes. The Share-VDE project (https://svde.org) is a collaborative discovery environment based on linked data. Explored in this talk are several lesser known and non-intuitive uses of Share-VDE linked data including discovery integration possibilities; data mining and machine learning process which targets Share-VDE enriched data. As brief records in our integrated library system receive improved cataloging from semi-automated subject indexing, we can improve traditional discovery and findability by better contextualizing the resources with linked data subject headings from FAST. The presentation will include screenshots and sample starter code that builds on Annif with Share-VDE data, among others.