Abstract
Windows, taken as snapshots of an RDF stream, are often applied to effectively characterize the semantics of the stream in RDF stream processing (RSP). Since some temporal relations among RDF triples in a window are possibly missing, however, windows could merely characterize the whole semantics of an RDF stream in a rough way. It is interesting to explore the temporal relations between RDF triples in RDF streams. In this paper, we extend continuous queries by introducing some important temporal relations to characterize inner connections among RDF triples, such as preorder relations between time points and time intervals. Furthermore, we demonstrate that those temporal relations are useful and effective in a traffic application.
This work is supported by the programs of the National Natural Science Foundation of China (61373165).
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Babcock, B., Babu, S., Datar, M., et al.: Models and issues in data stream systems. In: ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, pp. 1–16 (2002)
Margara, A., Urbani, J., Harmelen, F.V., et al.: Streaming the web: reasoning over dynamic data. Web Semant. Sci. Serv. Agents World Wide Web 25(1), 24–44 (2014)
Arasu, A., Babu, S., Widom, J.: CQL: a language for continuous queries over streams and relations. In: Lausen, G., Suciu, D. (eds.) DBPL 2003. LNCS, vol. 2921, pp. 1–19. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24607-7_1
Arasu, A., Babu, S., Widom, J.: The CQL continuous query language: semantic foundations and query execution. VLDB J. 121–142 (2006)
Gutierrez, C., Hurtado, C., Vaisman, A.: Temporal RDF. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 93–107. Springer, Heidelberg (2005). https://doi.org/10.1007/11431053_7
Gutierrez, C., Hurtado, C., Vaisman, A.: Introducing time into RDF. IEEE Trans. Knowl. Data Eng. 19(2) (2007)
Hayes, P.J., Patel-Schneider, P.F.: RDF Semantics 1.1. W3C Recommendation (2014)
Klyne, G., Carroll, J.J., McBride, B.: RDF 1.1 Concepts and Abstract Syntax. W3C Recommendation (2014)
Gutierrez, C., Hurtado, C., Mendelzon, A.O.: Formal aspects of querying RDF databases. In: Proceedings of SWDB, pp. 293–307 (2003)
Harris, S., Seaborne, A., Prud’hommeaus, E.: SPARQL 1.1 Query Language. W3C Recommendation (2013)
Barbieri, D.F., Braga, D., Ceri, S., et al.: Querying RDF streams with C-SPARQL. ACM SIGMOD Rec. 39(1), 20–26 (2010)
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). https://doi.org/10.1007/978-3-642-25073-6_24
Komazec, S., Cerri, D., Fensel, D.: Sparkwave: continuous schema-enhanced pattern matching over RDF data streams. In: ACM International Conference on Distributed Event-based Systems, pp. 58–68 (2012)
Allen, J.F.: Maintaining knowledge about temporal intervals. Readings Qual. Reason. Phys. Syst. 26(11), 361–372 (1983)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Yang, X., Rao, G., Feng, Z. (2017). Timely Detection of Temporal Relations in RDF Stream Processing Scenario. In: Song, S., Renz, M., Moon, YS. (eds) Web and Big Data. APWeb-WAIM 2017. Lecture Notes in Computer Science(), vol 10612. Springer, Cham. https://doi.org/10.1007/978-3-319-69781-9_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-69781-9_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-69780-2
Online ISBN: 978-3-319-69781-9
eBook Packages: Computer ScienceComputer Science (R0)