Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/308281 
Year of Publication: 
2023
Citation: 
[Journal:] International Journal on Digital Libraries [ISSN:] 1432-1300 [Volume:] 25 [Issue:] 2 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2023 [Pages:] 287-301
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
Retrievability measures the influence a retrieval system has on the access to information in a given collection of items. This measure can help in making an evaluation of the search system based on which insights can be drawn. In this paper, we investigate the retrievability in an integrated search system consisting of items from various categories, particularly focussing on datasets, publications and variables in a real-life digital library. The traditional metrics, that is, the Lorenz curve and Gini coefficient, are employed to visualise the diversity in retrievability scores of the three retrievable document types (specifically datasets, publications, and variables). Our results show a significant popularity bias with certain items being retrieved more often than others. Particularly, it has been shown that certain datasets are more likely to be retrieved than other datasets in the same category. In contrast, the retrievability scores of items from the variable or publication category are more evenly distributed. We have observed that the distribution of document retrievability is more diverse for datasets as compared to publications and variables.
Subjects: 
Retrievability
Dataset retrieval
Interactive IR
Diversity
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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