{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T16:53:10Z","timestamp":1773939190400,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686110","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T00:00:00Z","timestamp":1758499200000},"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":[[2025,9,22]]},"abstract":"<jats:p>This paper presents an ontology-based approach to proactive risk assessment in high-risk industrial environments, with a focus on molten metal handling in smelting plants. Distributed cognition theory serves as the theoretical framework, guiding the grounded theory and thematic analysis by framing collaboration and communication as emerging from interactions among operators, equipment, and the environment. This lens emphasized shared knowledge and distributed responsibilities, helping identify domain-relevant concepts critical for risk assessment. Expert insights from professionals at a Swedish smelting plant were systematically elicited and structured into an ontology to support proactive risk management. A prototype system integrating this ontology with a dynamic interface showed strong alignment with expert decision-making and safety assessments. Moreover, the system identified overlooked risks\u2014such as hazardous equipment containing molten metal\u2014and received positive user feedback. While tailored for smelting operations, the methodology has broader applicability to improving information sharing, decision-making, and safety in other socio-technical systems.<\/jats:p>","DOI":"10.3233\/faia250646","type":"book-chapter","created":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T14:36:51Z","timestamp":1758638211000},"source":"Crossref","is-referenced-by-count":1,"title":["Ontology-Based Risk Assessment in Smelting Plant Logistics"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-1151-4065","authenticated-orcid":false,"given":"John","family":"Granstr\u00f6m","sequence":"first","affiliation":[{"name":"Department of Computing Science, Ume\u00e5 University, SE-901 87, Ume\u00e5, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9379-4281","authenticated-orcid":false,"given":"Andreas","family":"Br\u00e4nnstr\u00f6m","sequence":"additional","affiliation":[{"name":"Department of Computing Science, Ume\u00e5 University, SE-901 87, Ume\u00e5, Sweden"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","HHAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA250646","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T14:36:51Z","timestamp":1758638211000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA250646"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,22]]},"ISBN":["9781643686110"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia250646","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,22]]}}}