{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T18:28:59Z","timestamp":1767637739745,"version":"3.48.0"},"reference-count":48,"publisher":"Maximum Academic Press","license":[{"start":{"date-parts":[[2024,3,14]],"date-time":"2024-03-14T00:00:00Z","timestamp":1710374400000},"content-version":"unspecified","delay-in-days":73,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["The Knowledge Engineering Review"],"published-print":{"date-parts":[[2024]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>In the previous two decades, Knowledge Graphs (KGs) have evolved, inspiring developers to build ever-more context-related KGs. Because of this development, Artificial Intelligence (AI) applications can now access open domain-specific information in a format that is both semantically rich and machine comprehensible. In this article, we introduce the XR4DRAMA framework. The KG of the XR4DRAMA framework can represent data for media preparation and disaster management. More specifically, the KG of the XR4DRAMA framework can represent information about: (a) Observations and Events (e.g., data collection of biometric sensors, information in photos and text messages), (b) Spatio-temporal (e.g., highlighted locations and timestamps), (c) Mitigation and response plans in crisis (e.g., first responder teams). In addition, we provide a mechanism that allows Points of Interest (POI) to be created or updated based on videos, photos, and text messages sent by users. For improved disaster management and media coverage of a location, POI serve as markers to journalists and first responders. A task creation mechanism is also provided for the disaster management scenario with the XR4DRAMA framework, which indicates to first responders and citizens what tasks need to be performed in case of an emergency. Finally, the XR4DRAMA framework has a danger zone creation mechanism. Danger zones are regions in a map that are considered as dangerous for citizens and first responders during a disaster management scenario and are annotated by a severity score. The last two mechanisms are based on a Decision Support System (DSS).<\/jats:p>","DOI":"10.1017\/s026988892400002x","type":"journal-article","created":{"date-parts":[[2024,3,14]],"date-time":"2024-03-14T04:29:48Z","timestamp":1710390588000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":2,"title":["XR4DRAMA a knowledge-based system for disaster management and media planning"],"prefix":"10.48130","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4569-503X","authenticated-orcid":false,"given":"Alexandros","family":"Vassiliades","sequence":"first","affiliation":[]},{"given":"Grigorios","family":"Stathopoulos-Kampilis","sequence":"additional","affiliation":[]},{"given":"Gerasimos","family":"Antzoulatos","sequence":"additional","affiliation":[]},{"given":"Spyridon","family":"Symeonidis","sequence":"additional","affiliation":[]},{"given":"Sotiris","family":"Diplaris","sequence":"additional","affiliation":[]},{"given":"Stefanos","family":"Vrochidis","sequence":"additional","affiliation":[]},{"given":"Nick","family":"Bassiliades","sequence":"additional","affiliation":[]},{"given":"Ioannis","family":"Kompatsiaris","sequence":"additional","affiliation":[]}],"member":"27968","published-online":{"date-parts":[[2024,3,14]]},"reference":[{"key":"S026988892400002X_ref21","doi-asserted-by":"crossref","first-page":"339","DOI":"10.3233\/AO-150155","article-title":"Towards ontology-driven situation-aware disaster management","volume":"10","author":"Moreira","year":"2015","journal-title":"Applied Ontology"},{"key":"S026988892400002X_ref35","doi-asserted-by":"crossref","first-page":"101096","DOI":"10.1016\/j.ijdrr.2019.101096","article-title":"A critical review of social resilience assessment frameworks in disaster management","volume":"35","author":"Saja","year":"2019","journal-title":"International Journal of Disaster Risk Reduction"},{"key":"S026988892400002X_ref39","doi-asserted-by":"crossref","unstructured":"Speer, R. , Chin, J. & Havasi, C. 2017. 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D. & Behzadan, A. H. 2020. Disaster impact information retrieval using deep learning object detection in crowdsourced drone footage. In EG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings, 134\u2013143."},{"key":"S026988892400002X_ref13","doi-asserted-by":"crossref","unstructured":"Gollob, E. , Kyrou, M. , Petrantonakis, P. C. & Kompatsiaris, I. 2022. From sensable to sensible spaces: Enhancing the sensibility of a home office using stress-aware deep reinforcement learning in virtual environments. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, CHI EA \u201922. 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Subjective street scene perceptions for shanghai with large-scale application of computer vision and machine learning, Technical report, EasyChair.","DOI":"10.1007\/978-981-16-5983-6_23"}],"container-title":["The Knowledge Engineering Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S026988892400002X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T14:42:24Z","timestamp":1767624144000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S026988892400002X\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":48,"alternative-id":["S026988892400002X"],"URL":"https:\/\/doi.org\/10.1017\/s026988892400002x","relation":{},"ISSN":["0269-8889","1469-8005"],"issn-type":[{"type":"print","value":"0269-8889"},{"type":"electronic","value":"1469-8005"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"\u00a9 The Author(s), 2024. Published by Cambridge University Press","name":"copyright","label":"Copyright","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http:\/\/creativecommons.org\/licenses\/by\/4.0\/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.","name":"license","label":"License","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}],"article-number":"e1"}}