Distributed Stream Consistency Checking

  • Shen Gao
  • Daniele Dell’AglioEmail author
  • Jeff Z. Pan
  • Abraham Bernstein
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10845)


Dealing with noisy data is one of the big issues in stream processing. While noise has been widely studied in settings where streams have simple schemas, e.g. time series, few solutions focused on streams characterized by complex data structures. This paper studies how to check consistency over large amounts of complex streams. Our proposed methods exploit reasoning to assess if portions of the streams are compliant to a reference conceptual model. To achieve scalability, our methods run on state-of-the-art distributed stream processing platforms, e.g. Apache Storm or Twitter Heron. Our first method computes the closure of Negative Inclusions (NIs) for DL-Lite ontologies and registers the NIs as queries. The second method compiles the ontology into a processing pipeline to evenly distribute the workload. Experiments compares the two methods and show that the second one improves the throughput up to 139% with the LUBM ontology and 330% with the NPD ontology.


  1. 1.
    Anicic, D., Fodor, P., Rudolph, S., Stojanovic, N.: EP-SPARQL: a unified language for event processing and stream reasoning. In: WWW, pp. 635–644. ACM (2011)Google Scholar
  2. 2.
    Arenas, M., Bertossi, L.E., Chomicki, J.: Consistent query answers in inconsistent databases. In: PODS, pp. 68–79. ACM Press (1999)Google Scholar
  3. 3.
    Artale, A., Calvanese, D., Kontchakov, R., Zakharyaschev, M.: The DL-Lite family and relations. J. Artif. Intell. Res. 36, 1–69 (2009)MathSciNetzbMATHGoogle Scholar
  4. 4.
    Baclawski, K., Kokar, M.M., Waldinger, R., Kogut, P.A.: Consistency checking of semantic web ontologies. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 454–459. Springer, Heidelberg (2002). Scholar
  5. 5.
    Barbieri, D.F., Braga, D., Ceri, S., Della Valle, E., Grossniklaus, M.: Querying RDF streams with C-SPARQL. SIGMOD Rec. 39(1), 20–26 (2010)CrossRefGoogle Scholar
  6. 6.
    Botoeva, E., Artale, A., Calvanese, D.: Query rewriting in DL-Lite\(^{({HN})}_{horn}\). In: Description Logics. CEUR Workshop Proceedings (2010)Google Scholar
  7. 7.
    Carbone, P., Katsifodimos, A., Ewen, S., Markl, V., Haridi, S., Tzoumas, K.: Apache Flink\(^{\rm {TM}}\): stream and batch processing in a single engine. IEEE Data Eng. Bull. 38(4), 28–38 (2015)Google Scholar
  8. 8.
    Cugola, G., Margara, A.: Processing flows of information: from data stream to complex event processing. ACM Comput. Surv. 44(3), 15 (2012)CrossRefGoogle Scholar
  9. 9.
    Dell’Aglio, D., Della Valle, E., van Harmelen, F., Bernstein, A.: Stream reasoning: a survey and outlook. Data Sci. 1(1–2), 59–83 (2017)Google Scholar
  10. 10.
    Flouris, G., Huang, Z., Pan, J.Z., Plexousakis, D., Wache, H.: Inconsistencies, negations and changes in ontologies. In: AAAI 2006, pp. 1295–1300 (2006)Google Scholar
  11. 11.
    Glimm, B., Horrocks, I., Motik, B., Stoilos, G., Wang, Z.: HermiT: an OWL 2 reasoner. J. Autom. Reason. 53(3), 245–269 (2014)CrossRefGoogle Scholar
  12. 12.
    Guo, Y., Pan, Z., Heflin, J.: LUBM: a benchmark for OWL knowledge base systems. J. Web Semant. 3(2–3), 158–182 (2005)CrossRefGoogle Scholar
  13. 13.
    Kontchakov, R., Lutz, C., Toman, D., Wolter, F., Zakharyaschev, M.: The combined approach to query answering in DL-Lite. In: KR 2010, pp. 247–257 (2010)Google Scholar
  14. 14.
    Kulkarni, S., Bhagat, N., Fu, M., Kedigehalli, V., Kellogg, C., Mittal, S., Patel, J.M., Ramasamy, K., Taneja, S.: Twitter Heron: stream processing at scale. In: SIGMOD, pp. 239–250 (2015)Google Scholar
  15. 15.
    Le Phuoc, D., Dao-Tran, M., Parreira, J.X., Hauswirth, M.: A native and adaptive approach for unified processing of linked streams and linked data. In: ISWC 2011, pp. 370–388 (2011)Google Scholar
  16. 16.
    Lecue, F., Pan., J.Z.: Consistent knowledge discovery from evolving ontologies. In: Proceedings of AAAI 2015 (2015)Google Scholar
  17. 17.
    Lembo, D., Ruzzi, M.: Consistent query answering over description logic ontologies. In: Marchiori, M., Pan, J.Z., Marie, C.S. (eds.) RR 2007. LNCS, vol. 4524, pp. 194–208. Springer, Heidelberg (2007). Scholar
  18. 18.
    Pan, J.Z., Calvanese, D., Eiter, T., Horrocks, I., Kifer, M., Lin, F., Zhao, Y. (eds.): Reasoning Web 2016. LNCS, vol. 9885. Springer, Cham (2017). Scholar
  19. 19.
    Paulheim, H., Gangemi, A.: Serving DBpedia with DOLCE – more than just adding a cherry on top. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9366, pp. 180–196. Springer, Cham (2015). Scholar
  20. 20.
    Paulheim, H., Stuckenschmidt, H.: Fast approximate A-box consistency checking using machine learning. In: Sack, H., Blomqvist, E., d’Aquin, M., Ghidini, C., Ponzetto, S.P., Lange, C. (eds.) ESWC 2016. LNCS, vol. 9678, pp. 135–150. Springer, Cham (2016). Scholar
  21. 21.
    Pérez-Urbina, H., Motik, B., Horrocks, I.: A comparison of query rewriting techniques for DL-Lite. In: Proceedings of DL 2009 (2009)Google Scholar
  22. 22.
    Ren, Y., Pan, J.Z.: Optimising ontology stream reasoning with truth maintenance system. In: CIKM 2011 (2011)Google Scholar
  23. 23.
    Rinne, M., Solanki, M., Nuutila, E.: RFID-based logistics monitoring with semantics-driven event processing. In: DEBS, pp. 238–245 (2016)Google Scholar
  24. 24.
    Skjæveland, M.G., Lian, E.H., Horrocks, I.: Publishing the Norwegian Petroleum Directorate’s FactPages as semantic web data. In: Alani, H., et al. (eds.) ISWC 2013. LNCS, vol. 8219, pp. 162–177. Springer, Heidelberg (2013). Scholar
  25. 25.
    Toshniwal, A., Taneja, S., Shukla, A., Ramasamy, K., Patel, J.M., Kulkarni, S., Jackson, J., Gade, K., Fu, M., Donham, J., Bhagat, N., Mittal, S., Ryaboy, D.V.: Storm@twitter. In: SIGMOD, pp. 147–156 (2014)Google Scholar
  26. 26.
    Volz, R., Staab, S., Motik, B.: Incrementally maintaining materializations of ontologies stored in logic databases. J. Data Semant. 2, 1–34 (2005)zbMATHGoogle Scholar
  27. 27.
    Wu, J., Lécé, F.: Towards consistency checking over evolving ontologies. In: CIKM, pp. 909–918. ACM (2014)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Shen Gao
    • 1
  • Daniele Dell’Aglio
    • 1
    Email author
  • Jeff Z. Pan
    • 2
  • Abraham Bernstein
    • 1
  1. 1.DDIS, Department of InformaticsUniversity of ZurichZurichSwitzerland
  2. 2.The University of AberdeenAberdeenUK

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