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Spatial Ontology-Mediated Query Answering over Mobility Streams

  • Thomas Eiter
  • Josiane Xavier Parreira
  • Patrik SchneiderEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10249)

Abstract

The development of (semi)-autonomous vehicles and communication between vehicles and infrastructure (V2X) will aid to improve road safety by identifying dangerous traffic scenes. A key to this is the Local Dynamic Map (LDM), which acts as an integration platform for static, semi-static, and dynamic information about traffic in a geographical context. At present, the LDM approach is purely database-oriented with simple query capabilities, while an elaborate domain model as captured by an ontology and queries over data streams that allow for semantic concepts and spatial relationships are still missing. To fill this gap, we present an approach in the context of ontology-mediated query answering that features conjunctive queries over DL-Lite\(_A\) ontologies allowing spatial relations and window operators over streams having a pulse. For query evaluation, we present a rewriting approach to ordinary DL-Lite\(_A\) that transforms spatial relations involving epistemic aggregate queries and uses a decomposition approach that generates a query execution plan. Finally, we report on experiments with two scenarios and evaluate our implementation based on the stream RDBMS PipelineDB.

Notes

Acknowledgements

Supported by the Austrian Research Promotion Agency project Industrienahe Dissertationen and the Austrian Science Fund projects P26471 and P27730.

References

  1. 1.
    Andreone, L., Brignolo, R., Damiani, S., Sommariva, F., Vivo, G., Marco, S.: Safespot final report. Technical report D8.1.1 (2010)Google Scholar
  2. 2.
    Anicic, D., Fodor, P., Rudolph, S., Stojanovic, N.: EP-SPARQL: a unified language for event processing and stream reasoning. In: Proceedings of WWW 2011, pp. 635–644 (2011)Google Scholar
  3. 3.
    Arasu, A., Babu, S., Widom, J.: The CQL continuous query language: semantic foundations and query execution. VLDB J. 15(2), 121–142 (2006)CrossRefGoogle Scholar
  4. 4.
    Artale, A., Kontchakov, R., Kovtunova, A., Ryzhikov, V., Wolter, F., Zakharyaschev, M.: First-order rewritability of temporal ontology-mediated queries. In: IJCAI 2015, pp. 2706–2712 (2015)Google Scholar
  5. 5.
    Barbieri, D.F., Braga, D., Ceri, S., Valle, E.D., Grossniklaus, M.: C-sparql: a continuous query language for rdf data streams. Int. J. Semant. Comput. 4(1), 3–25 (2010)CrossRefGoogle Scholar
  6. 6.
    Beck, H., Dao-Tran, M., Eiter, T., Fink, M.: LARS: A logic-based framework for analyzing reasoning over streams. In: Proceedings of AAAI 2015, pp. 1431–1438 (2015)Google Scholar
  7. 7.
    Borgwardt, S., Lippmann, M., Thost, V.: Temporalizing rewritable query languages over knowledge bases. J. Web Sem. 33, 50–70 (2015)CrossRefGoogle Scholar
  8. 8.
    Calbimonte, J.-P., Mora, J., Corcho, O.: Query rewriting in RDF stream processing. In: Sack, H., Blomqvist, E., d’Aquin, M., Ghidini, C., Ponzetto, S.P., Lange, C. (eds.) ESWC 2016. LNCS, vol. 9678, pp. 486–502. Springer, Cham (2016). doi: 10.1007/978-3-319-34129-3_30CrossRefGoogle Scholar
  9. 9.
    Calvanese, D., Giacomo, G.D., Lembo, D., Lenzerini, M., Rosati, R.: Tractable reasoning and efficient query answering in description logics: the dl-lite family. J. Autom. Reasoning 39(3), 385–429 (2007)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Calvanese, D., Kharlamov, E., Nutt, W., Thorne, C.: Aggregate queries over ontologies. In: Proceedings of ONISW 2008, pp. 97–104 (2008)Google Scholar
  11. 11.
    Eiter, T., Füreder, H., Kasslatter, F., Parreira, J.X., Schneider, P.: Towards a semantically enriched local dynamic map. In: Proc. 23rd World Congress on Intelligent Transport Systems (ITSWC-2016), Melbourne, October 10–14, 2016 (2016)Google Scholar
  12. 12.
    Eiter, T., Krennwallner, T., Schneider, P.: Lightweight spatial conjunctive query answering using keywords. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 243–258. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-38288-8_17CrossRefGoogle Scholar
  13. 13.
    Eiter, T., Parreira, J.X., Schneider, P.: Towards spatial ontology-mediated query answering over mobility streams. In: Proceedings of Stream Reasoning Workshop 2016, pp. 13–24 (2016)Google Scholar
  14. 14.
    Golab, L., Özsu, M.T.: Issues in data stream management. SIGMOD Rec. 32(2), 5–14 (2003)CrossRefGoogle Scholar
  15. 15.
    Klarman, S., Meyer, T.: Querying temporal databases via OWL 2 QL. In: Kontchakov, R., Mugnier, M.-L. (eds.) RR 2014. LNCS, vol. 8741, pp. 92–107. Springer, Cham (2014). doi: 10.1007/978-3-319-11113-1_7CrossRefGoogle Scholar
  16. 16.
    Koubarakis, M., Kyzirakos, K.: Modeling and querying metadata in the semantic sensor web: the model stRDF and the query language stSPARQL. In: Aroyo, L., Antoniou, G., Hyvönen, E., Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010. LNCS, vol. 6088, pp. 425–439. Springer, Heidelberg (2010). doi: 10.1007/978-3-642-13486-9_29CrossRefGoogle Scholar
  17. 17.
    Le-Phuoc, D., Dao-Tran, M., Xavier Parreira, J., Hauswirth, M.: A native and adaptive approach for unified processing of linked streams and linked data. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011. LNCS, vol. 7031, pp. 370–388. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-25073-6_24CrossRefGoogle Scholar
  18. 18.
    Maier, D.: The Theory of Relational Databases. Computer Science Press, Rockville (1983)zbMATHGoogle Scholar
  19. 19.
    Netten, B., Kester, L., Wedemeijer, H., Passchier, I., Driessen, B.: Dynamap: A dynamic map for road side its stations. In: Proceedings of ITS World Congress 2013 (2013)Google Scholar
  20. 20.
    Özçep, Ö.L., Möller, R., Neuenstadt, C.: Stream-query compilation with ontologies. In: Pfahringer, B., Renz, J. (eds.) AI 2015. LNCS (LNAI), vol. 9457, pp. 457–463. Springer, Cham (2015). doi: 10.1007/978-3-319-26350-2_40CrossRefGoogle Scholar
  21. 21.
    Perry, M., Jain, P., Sheth, A.P.: SPARQL-ST: extending SPARQL to support spatiotemporal queries. Geospatial Semant. Semant. Web 12, 61–86 (2011)CrossRefGoogle Scholar
  22. 22.
    Quoc, H.N.M., Le Phuoc, D.: An elastic and scalable spatiotemporal query processing for linked sensor data. In: Proceedings of Semantics 2015, pp. 17–24. ACM (2015)Google Scholar
  23. 23.
    Rodríguez-Muro, M., Kontchakov, R., Zakharyaschev, M.: Ontology-based data access: Ontop of databases. In: Alani, H., et al. (eds.) ISWC 2013. LNCS, vol. 8218, pp. 558–573. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-41335-3_35CrossRefGoogle Scholar
  24. 24.
    Stocker, M., Smith, M.: Owlgres: a scalable owl reasoner. In: Proceedings of OWLED 2008 (2008)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Thomas Eiter
    • 1
  • Josiane Xavier Parreira
    • 2
  • Patrik Schneider
    • 1
    • 2
    Email author
  1. 1.Vienna University of TechnologyViennaAustria
  2. 2.Siemens AG ÖsterreichViennaAustria

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