Metadata versus Full-Text: Tracking Users’ Electronic Theses and Dissertations (ETDs) Seeking Behavior

  • Daniel Gelaw AlemnehEmail author
  • Mark Phillips
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10766)


This presentation provides data from a recent research project at the University of North Texas (UNT) Libraries to better understand how users are discovering the electronic theses and dissertations (ETDs) in the UNT Libraries. To extract the specific requests for ETDs in the UNT Digital Library, the data was obtained from a server log-that contained more than 178 million lines of requests. From these requests, the search query was executed in an ambiguous way (not specific fielded searches) queries were extracted to create a dataset of item-query pairs. These item-query pairs were presented to the Solr full-text indexer that powers the search and retrieval side of the UNT Digital Library to report back on statistics, and help to explain whether a specific query was satisfied by either the ETDs full-text, metadata, or by both fields. The resulting data helps us understand how our users are arriving at a given ETD in the collection. Among other speculations, the role of metadata for the discovery process, and the possible overlap that is present between metadata and the full-text of the ETD itself will be analyzed and discussed.


Electronic theses and dissertations ETD discovery Metadata 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of North TexasDentonUSA

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