{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:34:04Z","timestamp":1760060044646,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T00:00:00Z","timestamp":1753660800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Semantically enriched trajectories have attracted growing interest in recent research, driven by the need for more expressive and context-aware movement data analysis. Two primary approaches have emerged for the storage and management of such data: moving object databases, which operate at the transactional or operational level, and trajectory data warehouses (TDWs), which support analytical processing within decision support systems. Conventional TDW methodologies typically model semantic aspects of trajectories by introducing new dimensions into the data warehouse schema. However, this approach often requires structural modifications to the schema in order to accommodate additional semantic attributes, potentially resulting in significant disruptions to the architecture and maintenance of the underlying decision support systems. To overcome this limitation, we propose a novel TDW model that supports dynamic and extensible integration of semantic aspects, without necessitating changes to the schema. This design enhances flexibility and promotes seamless adaptability to domain-specific requirements. To enable such extensibility, we propose an innovative approach to representing semantic trajectories by leveraging natural language processing (NLP) techniques. without relying on traditional spatiotemporal features. This enables the analysis of semantic movement patterns purely through textual context. Finally, we present a comprehensive framework that implements the proposed model in real-world application scenarios, demonstrating its practical extensibility.<\/jats:p>","DOI":"10.3390\/ijgi14080292","type":"journal-article","created":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T08:51:33Z","timestamp":1753692693000},"page":"292","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards an Extensible and Text-Oriented Analytical Semantic Trajectory Framework"],"prefix":"10.3390","volume":"14","author":[{"given":"Dami\u00e3o Ribeiro de","family":"Almeida","sequence":"first","affiliation":[{"name":"Federal Institute of Para\u00edba, Monteiro 58500000, Para\u00edba, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2200-1405","authenticated-orcid":false,"given":"Cl\u00e1udio de Souza","family":"Baptista","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Federal University of Campina Grande, Campina Grande 58429900, Para\u00edba, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabio Gomes de","family":"Andrade","sequence":"additional","affiliation":[{"name":"Federal Institute of Para\u00edba, Cajazeiras 58900000, Para\u00edba, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4921-0626","authenticated-orcid":false,"given":"Anselmo Cardoso de","family":"Paiva","sequence":"additional","affiliation":[{"name":"Applied Computing Center, Federal University of Maranh\u00e3o, S\u00e3o Lu\u00eds 65080805, Maranh\u00e3o, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"58295","DOI":"10.1109\/ACCESS.2018.2873779","article-title":"Big trajectory data: A survey of applications and services","volume":"6","author":"Kong","year":"2018","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Fileto, R., Raffaet\u00e0, A., Roncato, A., Sacenti, J.A., May, C., and Klein, D. 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