DevConnect 2024: Quantifying Metadata's Value in a Linked Data Landscape: Concepts, Questions, and Methods using SQLite and Python
As discovery products increasingly use linked data ontologies, libraries reflect on traditional metadata's value.
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As discovery products increasingly use linked data ontologies, libraries reflect on traditional metadata's value. Several studies at WVU Libraries explore whether metadata facilitates more precise retrieval than linked data alone:
- The first uses SQLite in Python to compare precision and relevance of retrieval using subject metadata and equivalent terms from a linked data ontology, EBSCO Discovery Service's "Concept Map."The methodology can be adapted to measure the performance of discovery products.
- A second study plans to use the newly released WorldCat Entities product. SQLite-based processes are used to quantify the increase in precision retrieval achieved by using attributes in a WorldCat Entity record over the WorldCat Entity label alone.
These studies, summarized and presented with examples of code, demonstrate how MARC and other traditional metadata is still valuable to evaluate and enrich linked data for discovery and reinforce the importance of dedicating library resources to its creation and management.
Presenter
Emily Fidelman
Head of Metadata Services
West Virginia University
DevConnect 2024
This webinar is part of DevConnect 2024, an annual OCLC program in which OCLC and library staff share API and technology insights with the library community.