Skip to main content
View expanded cover

European Knowledge Acquisition Workshop

EKAW 2016: Knowledge Engineering and Knowledge Management pp 145–162Cite as

A Query Model to Capture Event Pattern Matching in RDF Stream Processing Query Languages

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10024)

Abstract

The current state of the art in RDF Stream Processing (RSP) proposes several models and implementations to combine Semantic Web technologies with Data Stream Management System (DSMS) operators like windows. Meanwhile, only a few solutions combine Semantic Web and Complex Event Processing (CEP), which includes relevant features, such as identifying sequences of events in streams. Current RSP query languages that support CEP features have several limitations: EP-SPARQL can identify sequences, but its selection and consumption policies are not all formally defined, while C-SPARQL offers only a naive support to pattern detection through a timestamp function. In this work, we introduce an RSP query language, called RSEP-QL, which supports both DSMS and CEP operators, with a special interest in formalizing CEP selection and consumption policies. We show that RSEP-QL captures EP-SPARQL and C-SPARQL, and offers features going beyond the ones provided by current RSP query languages.

Keywords

  • Window Function
  • Event Mapping
  • Input Stream
  • Graph Pattern
  • Event Pattern

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This research has been supported by the Austrian Science Fund (FWF) project P26471, the Nano-tera.ch D1NAMO project, and the Marie Skłodowska-Curie Programme H2020-MSCA-IF-2014 under Grant No. 661180.

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-49004-5_10
  • Chapter length: 18 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-49004-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   139.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 1.

Notes

  1. 1.

    Cf. https://www.oasis-open.org/committees/soa-rm/faq.php.

  2. 2.

    Cf. https://www.w3.org/community/rsp/.

  3. 3.

    Cf. http://goo.gl/pqUSri (last access: July 7, 2016).

  4. 4.

    \( def \not \in I\cup L\cup B\) denoting the default graph. See [16] for the definitions of I, L, B.

  5. 5.

    Cf. https://www.w3.org/TR/sparql11-query for the whole list.

  6. 6.

    We do not tackle here the case where \(w \in I \cup V\), which is one of our future works.

  7. 7.

    http://tinyurl.com/ekaw2016-195-ext (Hosted by Google Drive).

References

  1. Agrawal, J., Diao, Y., Gyllstrom, D., Immerman, N.: Efficient pattern matching over event streams. In: SIGMOD, pp. 147–160 (2008)

    Google Scholar 

  2. Anicic, D.: Event processing and stream reasoning with ETALIS. Ph.D. thesis, Karlsruhe Institute of Technology (2011)

    Google Scholar 

  3. Anicic, D., Fodor, P., Rudolph, S., Stojanovic, N.: EP-SPARQL: a unified language for event processing and stream reasoning. In: WWW, pp. 635–644 (2011)

    Google Scholar 

  4. Arasu, A., Babu, S., Widom, J.: The CQL continuous query language: semantic foundations and query execution. VLDB J. 15(2), 121–142 (2006)

    CrossRef  Google Scholar 

  5. Babcock, B., Babu, S., Datar, M., Motwani, R., Widom, J.: Models and issues in data stream systems. In: PODS, pp. 1–16. ACM (2002)

    Google Scholar 

  6. Barbieri, D.F., Braga, D., Ceri, S., Della Valle, E., Grossniklaus, M.: C-SPARQL: a continuous query language for RDF data streams. Int. J. Semant. Comput. 4(1), 3–25 (2010)

    CrossRef  MATH  Google Scholar 

  7. Beck, H., Dao-Tran, M., Eiter, T., Fink, M.: LARS: a logic-based framework for analyzing reasoning over streams. In: AAAI, pp. 1431–1438 (2015)

    Google Scholar 

  8. Botan, I., Derakhshan, R., Dindar, N., Haas, L.M., Miller, R.J., Tatbul, N.: SECRET: a model for analysis of the execution semantics of stream processing systems. PVLDB 3(1), 232–243 (2010)

    Google Scholar 

  9. Calbimonte, J.P., Jeung, H., Corcho, Ó., Aberer, K.: Enabling query technologies for the semantic sensor web. Int. J. Semant. Web Inf. Syst. 8(1), 43–63 (2012)

    CrossRef  Google Scholar 

  10. Cugola, G., Margara, A.: Processing flows of information: from data stream to complex event processing. ACM Comput. Surv. 44(3), 15:1–15:62 (2011)

    Google Scholar 

  11. Dao-Tran, M., Beck, H., Eiter, T.: Contrasting RDF stream processing semantics. In: Qi, G., Kozaki, K., Pan, J.Z., Yu, S. (eds.) JIST 2015. LNCS, vol. 9544, pp. 289–298. Springer, Heidelberg (2016). doi:10.1007/978-3-319-31676-5_21

    CrossRef  Google Scholar 

  12. Dao-Tran, M., Le-Phuoc, D.: Towards enriching CQELS with complex event processing and path navigation. In: HiDeSt, pp. 2–14 (2015)

    Google Scholar 

  13. Dell’Aglio, D., Balduini, M., Della Valle, E.: On the need to include functional testing in RDF stream engine benchmarks. In: 10th ESWC 2013 Conference Workshops: BeRSys 2013, AImWD 2013 and USEWOD 2013 (2013)

    Google Scholar 

  14. Dell’Aglio, D., Valle, E.D., Calbimonte, J., Corcho, O.: RSP-QL semantics: a unifying query model to explain heterogeneity of RDF stream processing systems. Int. J. Semant. Web Inf. Syst. 10(4), 17–44 (2014)

    CrossRef  Google Scholar 

  15. Gutierrez, C., Hurtado, C., Vaisman, A.: Introducing time into RDF. IEEE Trans. Knowl. Data Eng. 19(2), 207–218 (2007)

    CrossRef  Google Scholar 

  16. Harris, S., Seaborne, A.: SPARQL 1.1 Query Language (2013). http://www.w3.org/TR/sparql11-query/

  17. Komazec, S., Cerri, D., Fensel, D.: Sparkwave: continuous schema-enhanced pattern matching over RDF data streams. In: DEBS, pp. 58–68 (2012)

    Google Scholar 

  18. Luckham, D.C.: The power of events - an introduction to complex event processing in distributed enterprise systems. ACM (2005)

    Google Scholar 

  19. 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, Part I. LNCS, vol. 7031, pp. 370–388. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  20. Rinne, M., Törmä, S., Nuutila, E.: SPARQL-based applications for RDF-encoded sensor data. In: SSN, vol. 904, pp. 81–96 (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Informatics, University of Zurich, Zurich, Switzerland

    Daniele Dell’Aglio

  2. Dipartimento di Elettronica, Informatica e Bioingegneria, Politecnico of Milano, Milano, Italy

    Daniele Dell’Aglio & Emanuele Della Valle

  3. Institute of Information Systems, Vienna University of Technology, Vienna, Austria

    Minh Dao-Tran

  4. Institute of Information Systems, HES-SO Valais-Wallis and LSIR, EPFL, Lausanne, Switzerland

    Jean-Paul Calbimonte

  5. Technical University of Berlin, Berlin, Germany

    Danh Le Phuoc

Authors
  1. Daniele Dell’Aglio
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Minh Dao-Tran
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jean-Paul Calbimonte
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Danh Le Phuoc
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Emanuele Della Valle
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Daniele Dell’Aglio .

Editor information

Editors and Affiliations

  1. Linköping University, Linköping, Sweden

    Eva Blomqvist

  2. University of Bologna, Bologna, Italy

    Paolo Ciancarini

  3. University of Bologna, Bologna, Italy

    Francesco Poggi

  4. University of Bologna, Bologna, Italy

    Fabio Vitali

Rights and permissions

Reprints and Permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Dell’Aglio, D., Dao-Tran, M., Calbimonte, JP., Le Phuoc, D., Della Valle, E. (2016). A Query Model to Capture Event Pattern Matching in RDF Stream Processing Query Languages. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds) Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10024. Springer, Cham. https://doi.org/10.1007/978-3-319-49004-5_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-49004-5_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49003-8

  • Online ISBN: 978-3-319-49004-5

  • eBook Packages: Computer ScienceComputer Science (R0)