{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T11:20:58Z","timestamp":1765279258810,"version":"3.30.2"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685618","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T00:00:00Z","timestamp":1733875200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,11]]},"abstract":"<jats:p>A significant portion of scientific knowledge resides within scholarly publications, both in print and digital formats. Recent advancements in natural language processing and information extraction techniques have enhanced the accessibility of this knowledge for further automated querying and processing. Structured and semantically-aware representations, such as ontologies, play a crucial role in simplifying and integrating access to this vast pool of knowledge. While several ontologies have been developed to capture the structure and discourse of scientific publications, there is a notable scarcity of ontologies for succinctly representing named entities that are present in scholarly documents. This paper introduces the Ontology for Named Entity Representation (OnNER) to address this gap. OnNER is designed to represent named entities \u2013 the terms identified and labeled using named entity recognition (NER) methods \u2013 from scholarly publications. The ontology provides a structured semantic representation of the named entities, how they are labeled, and where they occur. We discuss the overall design of OnNER, its integration with other ontologies, and demonstrate how the ontology facilitates advanced querying of named entities\u2019 presence and collocation within and across publications.<\/jats:p>","DOI":"10.3233\/faia241291","type":"book-chapter","created":{"date-parts":[[2024,12,13]],"date-time":"2024-12-13T10:21:24Z","timestamp":1734085284000},"source":"Crossref","is-referenced-by-count":1,"title":["OnNER: An Ontology for Semantic Representation of Named Entities in Scholarly Publications"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4013-3513","authenticated-orcid":false,"given":"Umayer","family":"Reza","sequence":"first","affiliation":[{"name":"School of Computing and Information Science, University of Maine, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0708-4070","authenticated-orcid":false,"given":"Xuelian","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computing and Information Science, University of Maine, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5331-5052","authenticated-orcid":false,"given":"Torsten","family":"Hahmann","sequence":"additional","affiliation":[{"name":"School of Computing and Information Science, University of Maine, USA"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Formal Ontology in Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA241291","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,13]],"date-time":"2024-12-13T10:21:24Z","timestamp":1734085284000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA241291"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,11]]},"ISBN":["9781643685618"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia241291","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,11]]}}}