Standardizing free-text data exemplified by two fields from the Immune Epitope Database

We developed a generalizable approach for normalization of free text as found in database fields with content on a specific topic. Creating and testing the rules took a one-time effort for a given field that can now be applied to data as it is being curated. The standardization achieved in two datasets tested produces significantly reduced variance in the content which enhances the findability and usability of that data, chiefly by improving search functionality and enabling linkages with formal ontologies.

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Publication Details

Journal
Journal of Biomedical Semantics
Published
2025-03-22
DOI
https://doi.org/10.1186/s13326-025-00324-7
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
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article

Standardizing free-text data exemplified by two fields from the Immune Epitope Database

James A. Overton, Bjoern Peters, Randi Vita, Sebastian Duesing et al.
Journal of Biomedical Semantics
Biomedical Text Mining and Ontologies
article

Standardizing free-text data exemplified by two fields from the Immune Epitope Database

James A. Overton, Bjoern Peters, Randi Vita, Sebastian Duesing, Jason W. Bennett
article en

Abstract

We developed a generalizable approach for normalization of free text as found in database fields with content on a specific topic. Creating and testing the rules took a one-time effort for a given field that can now be applied to data as it is being curated. The standardization achieved in two datasets tested produces significantly reduced variance in the content which enhances the findability and usability of that data, chiefly by improving search functionality and enabling linkages with formal ontologies.

Journal of Biomedical SemanticsVol. 16(1)
La Jolla Institute for Immunology (US), University of California San Diego (US)
Quality Education
Openalex Percentile: Top 95%
Biomedical Text Mining and Ontologies
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