Abstract
This chapter presents modeling and representation techniques for mobility data, focusing on semantic representations that build around the central concept of semantic trajectory. Moving from mobility data to enriched representations of positional information, associated with contextual data and furthermore with events that occur during the movement of an object, is critical to support advanced mobility analytics. Motivated by these requirements, this chapter describes the datAcron ontology that satisfies these requirements to a larger extent than previous works on semantic representations of trajectories, at multiple, interlinked levels of detail. In addition, we show that this ontology supports data transformations that are required for performing advanced analytics tasks, such as visual analytics, and we present use-case scenarios in the Air Traffic Management and maritime domains.
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References
Al-Dohuki, S., Wu, Y., Kamw, F., Yang, J., Li, X., Zhao, Y., Ye, X., Chen, W., Ma, C., Wang, F.: SemanticTraj: a new approach to interacting with massive taxi trajectories. IEEE Trans. Vis. Comput. Graph. 23(1), 11–20 (2017). http://doi.org/10.1109/TVCG.2016.2598416. http://doi.ieeecomputersociety.org/10.1109/TVCG.2016.2598416
Allen, J.F.: Maintaining knowledge about temporal intervals. Commun. ACM 26(11), 832–843 (1983). http://doi.org/10.1145/182.358434. http://doi.acm.org/10.1145/182.358434
Alvares, L.O., Bogorny, V., Kuijpers, B., de Macêdo, J.A.F., Moelans, B., Vaisman, A.A.: A model for enriching trajectories with semantic geographical information. In: GIS, p. 22 (2007)
Andrienko, N., Andrienko, G.: Visual analytics of movement: an overview of methods, tools and procedures. Inf. Vis. 12(1), 3–24 (2013). https://doi.org/10.1177/1473871612457601
Andrienko, G., Andrienko, N., Jankowski, P., Keim, D., Kraak, M., MacEachren, A., Wrobel, S.: Geovisual analytics for spatial decision support: setting the research agenda. Int. J. Geogr. Inf. Sci. 21(8), 839–857 (2007). https://doi.org/10.1080/13658810701349011
Andrienko, G., Andrienko, N., Demsar, U., Dransch, D., Dykes, J., Fabrikant, S.I., Jern, M., Kraak, M.J., Schumann, H., Tominski, C.: Space, time and visual analytics. Int. J. Geogr. Inf. Sci. 24(10), 1577–1600 (2010). https://doi.org/10.1080/13658816.2010.508043
Andrienko, G., Andrienko, N., Bak, P., Keim, D., Wrobel, S.: Visual Analytics of Movement. Springer Publishing Company, Incorporated, Berlin (2013)
Andrienko, G., Andrienko, N., Chen, W., Maciejewski, R., Zhao, Y.: Visual analytics of mobility and transportation: state of the art and further research directions. IEEE Trans. Intell. Transp. Syst. 18(8), 2232–2249 (2017). http://doi.org/10.1109/TITS.2017.2683539
Baglioni, M., de Macêdo, J.A.F., Renso, C., Trasarti, R., Wachowicz, M.: Towards semantic interpretation of movement behavior. In: Advances in GIScience, pp. 271–288. Springer, Berlin (2009)
Bogorny, V., Renso, C., de Aquino, A.R., de Lucca Siqueira, F., Alvares, L.O.: Constant - a conceptual data model for semantic trajectories of moving objects. Trans. GIS 18(1), 66–88 (2014)
Chu, D., Sheets, D.A., Zhao, Y., Wu, Y., Yang, J., Zheng, M., Chen, G.: Visualizing hidden themes of taxi movement with semantic transformation. In: Proceedings of the 2014 IEEE Pacific Visualization Symposium, PACIFICVIS ’14, pp. 137–144. IEEE Computer Society, Washington, DC (2014). http://dx.doi.org/10.1109/PacificVis.2014.50
Fileto, R., May, C., Renso, C., Pelekis, N., Klein, D., Theodoridis, Y.: The baquara2 knowledge-based framework for semantic enrichment and analysis of movement data. Data Knowl. Eng. 98, 104–122 (2015)
Hamad, K., Quiroga, C.: Geovisualization of archived ITS data-case studies. IEEE Trans. Intell. Transp. Syst. 17(1), 104–112 (2016). https://doi.org/10.1109/TITS.2015.2460995
Hu, Y., Janowicz, K., Carral, D., Scheider, S., Kuhn, W., Berg-Cross, G., Hitzler, P., Dean, M., Kolas, D.: A geo-ontology design pattern for semantic trajectories. In: Tenbrink, T., Stell, J., Galton, A., Wood, Z. (eds.) Spatial Information Theory, pp. 438–456. Springer International Publishing, Cham (2013)
Kotis, K., Vouros, G.A.: Human-centered ontology engineering: the HCOME methodology. Knowl. Inf. Syst. 10(1), 109–131 (2006)
Kraak, M., Ormeling, F.: Cartography: Visualization of Spatial Data, 3 edn. Guilford Publications, New York (2010)
Nogueira, T.P., Martin, H.: Querying semantic trajectory episodes. In: Proc. of MobiGIS, pp. 23–30 (2015)
Paiva Nogueira, T., Bezerra Braga, R., Martin, H.: An ontology-based approach to represent trajectory characteristics. In: Fifth International Conference on Computing for Geospatial Research and Application. Washington, DC (2014). https://hal.archives-ouvertes.fr/hal-01058269
Parent, C., Spaccapietra, S., Renso, C., Andrienko, G.L., Andrienko, N.V., Bogorny, V., Damiani, M.L., Gkoulalas-Divanis, A., de Macêdo, J.A.F., Pelekis, N., Theodoridis, Y., Yan, Z.: Semantic trajectories modeling and analysis. ACM Comput. Surv. 45(4), 42 (2013)
Peuquet, D.J.: It’s about time: a conceptual framework for the representation of temporal dynamics in geographic information systems. Ann. Assoc. Am. Geogr. 84(3), 441–461 (1994)
Santipantakis, G., Vouros, G., Glenis, A., Doulkeridis, C., Vlachou, A.: The datAcron ontology for semantic trajectories. In: ESWC-Poster Session (2017)
Santipantakis, G.M., Vouros, G.A., Doulkeridis, C., Vlachou, A., Andrienko, G.L., Andrienko, N.V., Fuchs, G., Garcia, J.M.C., Martinez, M.G.: Specification of semantic trajectories supporting data transformations for analytics: The datacron ontology. In: Proceedings of the 13th International Conference on Semantic Systems, SEMANTICS 2017, Amsterdam, 11–14 Sept 2017, pp. 17–24 (2017). https://doi.org/10.1145/3132218.3132225
Santipantakis, G., Doulkeridis, C., Vouros, G.A., Vlachou, A.: Masklink: Efficient link discovery for spatial relations via masking areas, arXiv:1803.01135v1 (2018)
Santipantakis, G.M., Glenis, A., Kalaitzian, N., Vlachou, A., Doulkeridis, C., Vouros, G.A.: FAIMUSS: flexible data transformation to RDF from multiple streaming sources. In: Proceedings of the 21th International Conference on Extending Database Technology, EDBT 2018, Vienna, 26–29 March 2018, pp. 662–665 (2018). https://doi.org/10.5441/002/edbt.2018.79
Santipantakis, G.M., Kotis, K.I., Vouros, G.A., Doulkeridis, C.: RDF-gen: Generating RDF from streaming and archival data. In: Proceedings of the 8th International Conference on Web Intelligence, Mining and Semantics, WIMS ’18, pp. 28:1–28:10. ACM, New York (2018). http://doi.org/10.1145/3227609.3227658. http://doi.acm.org/10.1145/3227609.3227658
Soltan Mohammadi, M., Mougenot, I., Thérèse, L., Christophe, F.: A semantic modeling of moving objects data to detect the remarkable behavior. In: AGILE 2017. Wageningen University, Chair group GIS & Remote Sensing (WUR-GRS), Wageningen (2017). https://hal.archives-ouvertes.fr/hal-01577679
Spaccapietra, S., Parent, C., Damiani, M.L., de Macêdo, J.A.F., Porto, F., Vangenot, C.: A conceptual view on trajectories. Data Knowl. Eng. 65(1), 126–146 (2008)
Vincenty, T.: Direct and inverse solutions of geodesics on the ellipsoid with application of nested equations. In: Survey Review XXII, pp. 88–93 (1975). https://doi.org/10.1179%2Fsre.1975.23.176.88. https://www.ngs.noaa.gov/PUBS_LIB/inverse.pdf
Vouros, G., Santipantakis, G., Doulkeridis, C., Vlachou, A., Andrienko, G., Andrienko, N., Fuchs, G., Martinez, M.G., Cordero, J.M.G.: The datacron ontology for the specification of semantic trajectories: specification of semantic trajectories for data transformations supporting visual analytics. J. Data Semant. 8 (2019). http://doi.org/10.1007/s13740-019-00108-0. http://link.springer.com/article/10.1007/s13740-019-00108-0
Wen, Y., Zhang, Y., Huang, L., Zhou, C., Xiao, C., Zhang, F., Peng, X., Zhan, W., Sui, Z.: Semantic modelling of ship behavior in harbor based on ontology and dynamic Bayesian network. ISPRS Int. J. Geo-Inf. 8(3) (2019). http://doi.org/10.3390/ijgi8030107. http://www.mdpi.com/2220-9964/8/3/107
Yan, Z., Macedo, J., Parent, C., Spaccapietra, S.: Trajectory ontologies and queries. Trans. GIS 12(s1), 75–91 (2008). http://doi.org/10.1111/j.1467-9671.2008.01137.x. https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-9671.2008.01137.x
Acknowledgements
The research work has been supported by the datAcron project, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 687591.
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Santipantakis, G.M., Vouros, G.A., Vlachou, A., Doulkeridis, C. (2020). Modeling Mobility Data and Constructing Large Knowledge Graphs to Support Analytics: The datAcron Ontology. In: Vouros, G., et al. Big Data Analytics for Time-Critical Mobility Forecasting. Springer, Cham. https://doi.org/10.1007/978-3-030-45164-6_5
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DOI: https://doi.org/10.1007/978-3-030-45164-6_5
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