Abstract
In many applications (like social or sensor networks) the information generated can be represented as a continuous stream of RDF items, where each item describes an application event (social network post, sensor measurement, etc). In this paper we focus on compressing RDF streams. In particular, we propose an approach for lossless RDF stream compression, named RDSZ (RDF Differential Stream compressor based on Zlib). This approach takes advantage of the structural similarities among items in a stream by combining a differential item encoding mechanism with the general purpose stream compressor Zlib. Empirical evaluation using several RDF stream datasets shows that this combination produces gains in compression ratios with respect to using Zlib alone.
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Álvarez-García, S., Brisaboa, N.R., Fernández, J.D., Martínez-Prieto, M.A.: Compressed k2-Triples for Full-In-Memory RDF Engines. In: AMCIS (2011)
Arias, J., Fernández, N., Sánchez, L., Fuentes-Lorenzo, D.: Ztreamy: A middleware for publishing semantic streams on the web. Web Semantics: Science, Services and Agents on the World Wide Web (in print)
Atemezing, G., Corcho, O., Garijo, D., Mora, J., Poveda-Villalón, M., Rozas, P., Vila-Suero, D., Villazón-Terrazas, B.: Transforming Meteorological Data into Linked Data. Semantic Web Journal (2012)
Barbieri, D.F., Braga, D., Ceri, S., Grossniklaus, M.: An execution environment for C-SPARQL queries. In: Proceedings of the 13th International Conference on Extending Database Technology, EDBT 2010, pp. 441–452 (2010)
Calbimonte, J.-P., Corcho, O., Gray, A.J.G.: Enabling ontology-based access to streaming data sources. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part I. LNCS, vol. 6496, pp. 96–111. Springer, Heidelberg (2010)
Fernández, J.D., Gutierrez, C., Martínez-Prieto, M.A.: RDF compression: basic approaches. In: Proceedings of the 19th International Conference on World Wide Web, WWW 2010, pp. 1091–1092 (2010)
Fernández, J.D., Martínez-Prieto, M.A., Gutiérrez, C., Polleres, A., Arias, M.: Binary RDF representation for publication and exchange (HDT). Web Semantics: Science, Services and Agents on the World Wide Web 19, 22–41 (2013)
Joshi, A., Hitzler, P., Dong, G.: Logical linked data compression. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 170–184. Springer, Heidelberg (2013)
Le-Phuoc, D., Nguyen Mau Quoc, H., Le Van, C., Hauswirth, M.: Elastic and scalable processing of linked stream data in the cloud. In: Alani, H., Kagal, L., Fokoue, A., Groth, P., Biemann, C., Parreira, J.X., Aroyo, L., Noy, N., Welty, C., Janowicz, K. (eds.) ISWC 2013, Part I. LNCS, vol. 8218, pp. 280–297. Springer, Heidelberg (2013)
Deutsch, P., Gailly, J.-L. (eds.): ZLIB Compressed Data Format Specification version 3.3. Internet RFC 1950 (May 1996)
Deutsch, P. (ed.): DEFLATE Compressed Data Format Specification version 1.3. Internet RFC 1951 (May 1996)
Urbani, J., Maassen, J., Drost, N., Seinstra, F., Bal, H.: Scalable RDF data compression with MapReduce. Concurrency and Computation: Practice and Experience 25(1), 24–39 (2013)
Valle, E.D., Ceri, S., Harmelen, F.V., Fensel, D.: It’s a streaming world! reasoning upon rapidly changing information. IEEE Intelligent Systems 24(6), 83–89 (2009)
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Fernández, N., Arias, J., Sánchez, L., Fuentes-Lorenzo, D., Corcho, Ó. (2014). RDSZ: An Approach for Lossless RDF Stream Compression. In: Presutti, V., d’Amato, C., Gandon, F., d’Aquin, M., Staab, S., Tordai, A. (eds) The Semantic Web: Trends and Challenges. ESWC 2014. Lecture Notes in Computer Science, vol 8465. Springer, Cham. https://doi.org/10.1007/978-3-319-07443-6_5
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DOI: https://doi.org/10.1007/978-3-319-07443-6_5
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