Intersection-based Spatial Annotation of Trajectories with Linked Data
Abstract
Smart cities are characterized by providing new services through Information and Communications Technologies. However, it is important to gather data from citizens to discover new knowledge about certain aspects of a city. One example of a rich domain for collecting data in a smart city is exploring the use of mobile fitness applications. Users usually record outdoor activities in the form of trajectories, which can later be acquired for further analysis. In this work, we leverage Semantic Web technologies to propose an annotation algorithm that segments trajectories according to their spatial context. We demonstrate how the method works and the impact of OpenStreetMap related ontologies in the annotation process.
References
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Ballatore, Andrea, Michela Bertolotto, and David C.Wilson (2012). “Geographic Knowledge Extraction and Semantic Similarity in OpenStreetMap”. In: Knowledge and Information Systems 37.1, pp. 61–81. DOI: http://dx.doi.org/10.1007/s10115-012-0571-0.
Bennett, Jonathan (2010). OpenStreetMap. Birmingham, UK: Packt Publishing, p. 252. ISBN: 9781847197504.
Cocchia, Annalisa (2014). “Smart and Digital City: A Systematic Literature Review”. In: Smart City: How to Create Public and Economic Value with High Technology in Urban Space. Ed. by Renata Paola Dameri and Camille Rosenthal-Sabroux. Cham: Springer International Publishing, pp. 13–43. ISBN: 978-3-319-06160-3.DOI: 10 . 1007 / 978 - 3 - 319 - 06160 - 3 _ 2. URL: http : / / link .springer.com/10.1007/978-3-319-06160-3%7B%5C_%7D2.
Dodge, Somayeh, Robert Weibel, and Anna-Katharina Lautenschütz (2008). “Towards a taxonomy of movement patterns”. In: Information Visualization 7.3-4, pp. 240–252. ISSN: 1473-8716. DOI: 10.1057/palgrave.ivs.9500182. URL:http://ivi.sagepub.com/lookup/doi/10.1057/palgrave.ivs.9500182.
Furletti, Barbara, Paolo Cintia, Chiara Renso, and Laura Spinsanti (2013). “Inferring human activities from GPS tracks”. In: Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing - UrbComp ’13. New York, New York, USA: ACM Press, p. 1. ISBN: 9781450323314. DOI: 10.1145/2505821.2505830. URL: http : / / dl . acm . org / citation . cfm ? doid =2505821.2505830.
Nogueira, Tales P., Reinaldo B. Braga, Carina T. de Oliveira, and Hervé Martin (Feb. 2018). “FrameSTEP: A framework for annotating semantic trajectories based on episodes”. In: Expert Systems with Applications 92, pp. 533–545. ISSN: 09574174. DOI: 10.1016/j.eswa.2017.10.004. URL: http://linkinghub.elsevier.com/retrieve/pii/S0957417417306796.
Ragone, Azzurra, Tommaso Di Noia, Vito Walter Anelli, Andrea Calì, and Matteo Palmonari (2016). “Exposing Open Street Map in the Linked Data cloud”. In: Proceedings of the 29th International Conference on Industrial, Engineering & other Applications of Applied Intelligent Systems. URL: http://www-ictserv.poliba.it/sisinflab/publication%20s/2016/RDACP16.
Spaccapietra, Stefano, Christine Parent, and Laura Spinsanti (2013). “Trajectories and Their Representations”. In: Mobility Data: Modeling, Management, and Understanding. Ed. by Chiara Renso, Stefano Spaccapietra, and Esteban Zimányi. Cambridge University Press, pp. 3–22. ISBN: 9781139128926.
Stadler, Claus, Jens Lehmann, Konrad Höffner, and Sören Auer (2012). “LinkedGeoData: A Core for aWeb of Spatial Open Data”. In: Semantic Web 3.4, pp. 333–354. DOI:10.3233/SW- 2011- 0052. URL: http://iospress.metapress.com/content/141W054666871326.
Yan, Zhixian, Dipanjan Chakraborty, Christine Parent, Stefano Spaccapietra, and Karl Aberer (2011). “SeMiTri: A Framework for Semantic Annotation of Heterogeneous Trajectories”. In: Proceedings of the 14th International Conference on Extending Database Technology - EDBT/ICDT ’11. New York, New York, USA: ACM Press, p. 259. ISBN: 9781450305280. DOI: 10 . 1145 / 1951365 . 1951398. URL: http://portal.acm.org/citation.cfm?doid=1951365.1951398.
— (2012). “Semantic Trajectories: Mobility Data Computation and Annotation”. In: ACM Transactions on Intelligent Systems and Technology (TIST) 4.2, 39:1–39:38. DOI: 10.1145/2483669.2483682.
Zheng, Yu (2015). “Trajectory Data Mining: An Overview”. In: ACM Trans. On Intelligent Systems and Technology 6.3. DOI: 10.1145/2743025.
Published
2019-07-19
How to Cite
NOGUEIRA, Tales; MARTIN, Hervé; ANDRADE , Rossana.
Intersection-based Spatial Annotation of Trajectories with Linked Data. In: BRAZILIAN WORKSHOP ON INTELLIGENT CITIES (WBCI), 2. , 2019, Belém.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
DOI: https://doi.org/10.5753/wbci.2019.6750.
