skip to main content
10.1145/2335484.2335491acmconferencesArticle/Chapter ViewAbstractPublication PagesdebsConference Proceedingsconference-collections
research-article

Sparkwave: continuous schema-enhanced pattern matching over RDF data streams

Published: 16 July 2012 Publication History

Abstract

Data streams, often seen as sources of events, have appeared on the Web. Stream processing on the Web needs however to cope with the typical openness and heterogeneity of the Web environment. Semantic Web technologies, meant to facilitate data integration in an open environment, can help to address heterogeneities across multiple streams. In this paper we present Sparkwave, an approach for continuous pattern matching over RDF data streams. Sparkwave is based on the Rete algorithm, which allows efficient and truly continuous processing of data streams. Sparkwave is able to leverage RDF schema information associated to data streams to compute entailments, so that implicit knowledge is taken into account for pattern matching. In addition, it further extends Rete to support time-based sliding windows and static data instances, to cope with the streaming nature of processed data and real-world use cases.

References

[1]
D. J. Abadi, D. Carney, U. ÃGetintemel, M. Cherniack, C. Convey, S. Lee, M. Stonebraker, N. Tatbul, and S. Zdonik. Aurora: A New Model and Architecture for Data Stream Management. The VLDB Journal, 12:120--139, 2003.
[2]
R. Adaikkalavan and S. Chakravarthy. SnoopIB: Interval-Based Event Specification and Detection for Active Databases. In Advances in Databases and Information Systems, volume 2798 of Lecture Notes in Computer Science, pages 190--204. Springer Berlin/Heidelberg, 2003.
[3]
J. F. Allen and G. Ferguson. Actions and Events in Interval Temporal Logic. Technical report, University of Rochester, 1994.
[4]
D. Anicic, P. Fodor, S. Rudolph, and N. Stojanovic. EP-SPARQL: A Unified Language for Event Processing and Stream Reasoning. In Proc. of the 20th Int, Conf. on World Wide Web, WWW '11, pages 635--644, New York, NY, USA, 2011. ACM.
[5]
D. Anicic, P. Fodor, S. Rudolph, R. Stühmer, N. Stojanovic, and R. Studer. ETALIS: Rule-Based Reasoning in Event Processing. In Reasoning in Event-Based Distributed Systems, volume 347 of Studies in Computational Intelligence, pages 99--124. Springer, 2011.
[6]
A. Arasu, B. Babcock, S. Babu, J. Cieslewicz, M. Datar, K. Ito, R. Motwani, U. Srivastava, and J. Widom. STREAM: The Stanford Data Stream Management System. Technical Report 2004--20, Stanford InfoLab, 2004.
[7]
D. Barbieri, D. Braga, S. Ceri, E. Della Valle, and M. Grossniklaus. Incremental Reasoning on Streams and Rich Background Knowledge. In Proc. of 7th Extended Semantic Web Conference (ESWC 2010), volume 6088 of LNCS, pages 1--15. Springer, 2010.
[8]
D. F. Barbieri, D. Braga, S. Ceri, E. Della Valle, and M. Grossniklaus. C-SPARQL: a Continuous Query Language for RDF Data Streams. Int. J. Semantic Computing, 4(1):3--25, 2010.
[9]
C. Bizer and A. Schultz. The Berlin SPARQL Benchmark. International Journal On Semantic Web and Information Systems, 5(2):1--24, 2009.
[10]
A. Bolles, M. Grawunder, and J. Jacobi. Streaming SPARQL - Extending SPARQL to Process Data Streams. In The Semantic Web: Research and Applications, volume 5021 of Lecture Notes in Computer Science, pages 448--462. Springer Berlin/Heidelberg, 2008.
[11]
I. Celino, D. Dell'Aglio, E. Della Valle, Y. Huang, T. Lee, S. Park, and V. Tresp. Making Sense of Location Based Micro-posts Using Stream Reasoning. In Proceedings of the 1st Workshop on Making Sense of Microposts (#MSM2011), pages 13--18, May 2011.
[12]
S. Chakravarthy, V. Krishnaprasad, E. Anwar, and S.-K. Kim. Composite Events for Active Databases: Semantics, Contexts and Detection. In Proc. of 20th Int. Conf. on Very Large Data Bases, VLDB '94, pages 606--617. Morgan Kaufmann, 1994.
[13]
E. Della Valle, S. Ceri, F. van Harmelen, and D. Fensel. It's a Streaming World! Reasoning upon Rapidly Changing Information. IEEE Intelligent Systems, 24:83--89, November 2009.
[14]
R. J. Doorenbos. Production Matching for Large Learning Systems. PhD thesis, Carnegie Mellon University, Pittsbrurg, PA, 1995.
[15]
C. L. Forgy. Rete: A fast algorithm for the many pattern/many object pattern match problem. Artificial Intelligence, 19:17--37, 1982.
[16]
B. Glimm, A. Hogan, M. Krötzsch, and A. Polleres. OWL: Yet to arrive on the Web of Data? In Proceedings of Linked Data on the Web (LDOW2012) Workshop. CEUR Workshop Proceedings, 2012.
[17]
C. Grady, F. Highland, C. Iwaskiw, and M. Pfeifer. System and Method For Building a Computer-Based RETE Pattern Matching Network. Technical report, IBM Corp., Armonk, N. Y., 1994.
[18]
S. Groppe, J. Groppe, D. Kukulenz, and V. Linnemann. A SPARQL Engine for Streaming RDF Data. In Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System, pages 167--174, Washington, DC, USA, 2007. IEEE Computer Society.
[19]
P. Hayes. RDF Semantics. W3C Recommendation, W3C, Feb. 2004.
[20]
G. Klyne and J. J. Carroll. Resource Description Framework (RDF): Concepts and Abstract Syntax. W3C Recommendation, W3C, Feb. 2004.
[21]
D. Le-Phuoc, M. Dao-Tran, J. Xavier Parreira, and M. Hauswirth. A Native and Adaptive Approach for Unified Processing of Linked Streams and Linked Data. In Proceedings of the 10th International Semantic Web Conference, volume 7031 of Lecture Notes in Computer Science, pages 370--388. Springer Berlin/Heidelberg, 2011.
[22]
D. C. Luckham. The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 2001.
[23]
M. Perry, P. Jain, and A. P. Sheth. SPARQL-ST: Extending SPARQL to Support Spatiotemporal Queries. In Geospatial Semantics and the Semantic Web, volume 12 of Semantic Web and Beyond, pages 61--86. Springer US, 2011.
[24]
J. F. Sequeda, O. Corcho, and A. Gomez-Perez. Linked Stream Data: a short paper. In 2nd Semantic Sensor Network Workshop. CEUR Workshop Proceedings, 2009.
[25]
A. Sheth, C. Henson, and S. S. Sahoo. Semantic Sensor Web. IEEE Internet Computing, 12(4):78--83, july-august 2008.
[26]
H. Stuckenschmidt and J. Broekstra. Time-Space Trade-offs in Scaling up RDF Schema Reasoning. In WISE Workshops, volume 3807 of LNCS, pages 172--181. Springer, 2005.
[27]
J. Tappolet and A. Bernstein. Applied Temporal RDF: Efficient Temporal Querying of RDF Data with SPARQL. In The Semantic Web: Research and Applications, volume 5554 of Lecture Notes in Computer Science, pages 308--322. Springer Berlin/Heidelberg, 2009.
[28]
K. Walzer, T. Breddin, and M. Groch. Relative temporal constraints in the Rete algorithm for complex event detection. In Proceedings of the second international conference on Distributed event-based systems, DEBS '08, pages 147--155, New York, NY, USA, 2008. ACM.
[29]
K. Walzer, M. Groch, and T. Breddin. Time to the Rescue - Supporting Temporal Reasoning in the Rete Algorithm for Complex Event Processing. In Proceedings of the 19th international conference on Database and Expert Systems Applications, DEXA '08, pages 635--642, Berlin, Heidelberg, 2008. Springer-Verlag.
[30]
K. Walzer, T. Heinze, and A. Klein. Event Lifetime Calculation based on Temporal Relationships. In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD 2009), pages 269--274. INSTICC Press, October 2009.

Cited By

View all
  • (2024)RDF Stream Taxonomy: Systematizing RDF Stream Types in Research and PracticeElectronics10.3390/electronics1313255813:13(2558)Online publication date: 29-Jun-2024
  • (2024)A holistic view over ontologies for Streaming Linked DataSemantic Web10.3233/SW-24357015:5(2005-2033)Online publication date: 9-Oct-2024
  • (2024)MWP: Multi-Window Parallel Evaluation of Regular Path Queries on Streaming GraphsProceedings of the ACM on Management of Data10.1145/36392602:1(1-26)Online publication date: 26-Mar-2024
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
DEBS '12: Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
July 2012
410 pages
ISBN:9781450313155
DOI:10.1145/2335484
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 July 2012

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. RDF
  2. Rete
  3. inference
  4. pattern matching
  5. semantic web
  6. stream processing
  7. stream reasoning

Qualifiers

  • Research-article

Funding Sources

Conference

DEBS '12

Acceptance Rates

Overall Acceptance Rate 145 of 583 submissions, 25%

Upcoming Conference

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)4
  • Downloads (Last 6 weeks)0
Reflects downloads up to 20 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2024)RDF Stream Taxonomy: Systematizing RDF Stream Types in Research and PracticeElectronics10.3390/electronics1313255813:13(2558)Online publication date: 29-Jun-2024
  • (2024)A holistic view over ontologies for Streaming Linked DataSemantic Web10.3233/SW-24357015:5(2005-2033)Online publication date: 9-Oct-2024
  • (2024)MWP: Multi-Window Parallel Evaluation of Regular Path Queries on Streaming GraphsProceedings of the ACM on Management of Data10.1145/36392602:1(1-26)Online publication date: 26-Mar-2024
  • (2023)Context-aware query derivation for IoT data streams with DIVIDE enabling privacy by designSemantic Web10.3233/SW-22328114:5(893-941)Online publication date: 8-May-2023
  • (2022)Evaluating Complex Queries on Streaming Graphs2022 IEEE 38th International Conference on Data Engineering (ICDE)10.1109/ICDE53745.2022.00025(272-285)Online publication date: May-2022
  • (2022)Optimization of Subgraph Matching over Knowledge Graph Based on Subgraph Indexing2022 5th International Conference on Artificial Intelligence and Big Data (ICAIBD)10.1109/ICAIBD55127.2022.9820592(543-546)Online publication date: 27-May-2022
  • (2022)Semantic Stream Processing and ReasoningEncyclopedia of Big Data Technologies10.1007/978-3-319-63962-8_287-2(1-10)Online publication date: 16-Mar-2022
  • (2022)Web Stream Processing Systems and BenchmarksStreaming Linked Data10.1007/978-3-031-15371-6_5(109-138)Online publication date: 22-Aug-2022
  • (2020)Real-Time Compliant Stream Processing Agents for Physical RehabilitationSensors10.3390/s2003074620:3(746)Online publication date: 29-Jan-2020
  • (2020)A stream reasoning framework based on a multi-agents modelProceedings of the 35th Annual ACM Symposium on Applied Computing10.1145/3341105.3374111(509-512)Online publication date: 30-Mar-2020
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media