Abstract
Movement understanding frequently requires further information and knowledge than what can be obtained from bare spatio-temporal traces. Despite recent progress in trajectory data management, there is still a gap between the spatio-temporal aspects and the semantics involved. This gap hinders trajectory analysis benefiting from growing collections of linked data, with well-defined and widely agreed semantics, already available on the Web. This article introduces Baquara, an ontology with rich constructs, associated with a system architecture and an approach to narrow this gap. The Baquara ontology functions as a conceptual framework for semantic enrichment of movement data with annotations based on linked data. The proposed architecture and approach reveal new possibilities for trajectory analysis, using database management systems and triple stores extended with spatial data and operators. The viability of the proposal and the expressiveness of the Baquara ontology and enabled queries are investigated in a case study using real sets of trajectories and linked data.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Battle, M., Kolas, D.: Enabling the Geospacial Semantic Web with Parliament and GeoSPARQL. Semantic Web Journal 3(4), 355–370 (2012)
Bogorny, V., Renso, C., Aquino, A., Siqueira, F.L., Alvares, L.O.: CONSTAnT - A Conceptual Data Model for Semantic Trajectories of Moving Objects. Transactions in GIS 8(2) (2013)
Cohen, W.W., Ravikumar, P.D., Fienberg, S.E.: A Comparison of String Distance Metrics for Name-Matching Tasks. In: IIWeb, pp. 73–78 (2003)
Giannotti, F., Nanni, M., Pedreschi, D., Pinelli, F., Renso, C., Rinzivillo, S., Trasarti, R.: Unveiling the complexity of human movement by querying and mining massive trajectory data. The VLDB Journal 20(5), 695–719 (2011)
Navarro, G.: A guided tour to approximate string matching. ACM Computing Surveys 33(1), 31–88 (2001)
Kyzirakos, K., Karpathiotakis, M., Koubarakis, M.: Strabon: A Semantic Geospatial DBMS. In: Cudré-Mauroux, P., Heflin, J., Sirin, E., Tudorache, T., Euzenat, J., Hauswirth, M., Parreira, J.X., Hendler, J., Schreiber, G., Bernstein, A., Blomqvist, E. (eds.) ISWC 2012, Part I. LNCS, vol. 7649, pp. 295–311. Springer, Heidelberg (2012)
Mountain, D., Raper, J.F.: Modelling human spatio-temporal behaviour: a challenge for location-based services. In: 6th Int. Conf. on GeoComputation, Brisbane, Australia, pp. 24–26 (2001)
Parent, C., Spaccapietra, S., Renso, C., Andrienko, G., Andrienko, N., Bogorny, V., Damiani, M.L., Gkoulalas-divanis, A., Macedo, J., Pelekis, N., Theodoridis, Y., Yan, Z.: Semantic trajectories modeling and analysis. ACM Computing Surveys 45 (2013)
Parent, C., Spaccapietra, S., Zimányi, E.: Conceptual Modeling for Traditional and Spatio-Temporal Applications: The MADS Approach. Springer (2006)
Pelekis, N., Frentzos, E., Giatrakos, N., Theodoridis, Y.: HERMES: aggregative LBS via a trajectory DB engine. In: SIGMOD Conf., pp. 1255–1258 (2008)
Renso, C., Baglioni, M., de Macedo, J.A.F., Trasarti, R., Wachowicz, M.: How you move reveals who you are: understanding human behavior by analyzing trajectory data. Knowledge and Information System Journal (KAIS), 1–32 (June 2012)
Spaccapietra, S., Parent, C., Damiani, M.L., de Macedo, J.A., Porto, F., Vangenot, C.: A conceptual view on trajectories. Data and Knowledge Engineering 65(1), 126–146 (2008)
Yan, Z., Macedo, J., Parent, C., Spaccapietra, S.: Trajectory Ontologies and Queries. Transactions in GIS, 12(suppl. 1), 75–91 (2008)
Yao, B., Li, F., Hadjieleftheriou, M., Hou, K.: Approximate string search in spatial databases. In: Int. IEEE Conf. on Data Engineering (ICDE), pp. 545–556 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fileto, R., Krüger, M., Pelekis, N., Theodoridis, Y., Renso, C. (2013). Baquara: A Holistic Ontological Framework for Movement Analysis Using Linked Data. In: Ng, W., Storey, V.C., Trujillo, J.C. (eds) Conceptual Modeling. ER 2013. Lecture Notes in Computer Science, vol 8217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41924-9_28
Download citation
DOI: https://doi.org/10.1007/978-3-642-41924-9_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41923-2
Online ISBN: 978-3-642-41924-9
eBook Packages: Computer ScienceComputer Science (R0)