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Text-based annotation of scientific images using Wikimedia categories

  • The reuse of scientific raw data is a key demand of Open Science. In the project NOA we foster reuse of scientific images by collecting and uploading them to Wikimedia Commons. In this paper we present a text-based annotation method that proposes Wikipedia categories for open access images. The assigned categories can be used for image retrieval or to upload images to Wikimedia Commons. The annotation basically consists of two phases: extracting salient keywords and mapping these keywords to categories. The results are evaluated on a small record of open access images that were manually annotated.

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Author:Frieda JosiORCiD, Christian WartenaORCiDGND, Jean CharbonnierORCiD
URN:urn:nbn:de:bsz:960-opus4-12488
DOI:https://doi.org/10.1007/978-3-319-99133-7_20
ISBN:978-3-319-99132-0
ISBN:978-3-319-99133-7
Parent Title (English):Elloumi M. et al. (eds): Database and Expert Systems Applications. DEXA 2018. Communications in Computer and Information Science, vol. 903
Publisher:Springer
Place of publication:Cham
Document Type:Conference Proceeding
Language:English
Year of Completion:2018
Release Date:2018/09/05
Tag:Scientific image search; Text annotation; Wikipedia categories
First Page:243
Last Page:253
Note:
The final authenticated version is available online at https://doi.org/10.1007/978-3-319-99133-7_20
Institutes:Fakultät III - Medien, Information und Design
DDC classes:020 Bibliotheks- und Informationswissenschaft
Licence (German):License LogoUrheberrechtlich geschützt