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A catalogue with semantic annotations makes multilabel datasets FAIR

التفاصيل البيبلوغرافية
العنوان: A catalogue with semantic annotations makes multilabel datasets FAIR
المؤلفون: Ana Kostovska, Jasmin Bogatinovski, Sašo Džeroski, Dragi Kocev, Panče Panov
المصدر: Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
بيانات النشر: Nature Portfolio, 2022.
سنة النشر: 2022
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: Abstract Multilabel classification (MLC) is a machine learning task where the goal is to learn to label an example with multiple labels simultaneously. It receives increasing interest from the machine learning community, as evidenced by the increasing number of papers and methods that appear in the literature. Hence, ensuring proper, correct, robust, and trustworthy benchmarking is of utmost importance for the further development of the field. We believe that this can be achieved by adhering to the recently emerged data management standards, such as the FAIR (Findable, Accessible, Interoperable, and Reusable) and TRUST (Transparency, Responsibility, User focus, Sustainability, and Technology) principles. We introduce an ontology-based online catalogue of MLC datasets originating from various application domains following these principles. The catalogue extensively describes many MLC datasets with comprehensible meta-features, MLC-specific semantic descriptions, and different data provenance information. The MLC data catalogue is available at: http://semantichub.ijs.si/MLCdatasets .
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-022-11316-3
URL الوصول: https://doaj.org/article/cb1b9cda916845a097319c3929a5fa50
رقم الأكسشن: edsdoj.b1b9cda916845a097319c3929a5fa50
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20452322
DOI:10.1038/s41598-022-11316-3