Abstract
One of the main advantages of using semantically annotated data is that machines can reason on it, deriving implicit knowledge from explicit information. In this context, materializing every possible implicit derivation from a given input can be computationally expensive, especially when considering large data volumes.
Most of the solutions that address this problem rely on the assumption that the information is static, i.e., that it does not change, or changes very infrequently. However, the Web is extremely dynamic: online newspapers, blogs, social networks, etc., are frequently changed so that outdated information is removed and replaced with fresh data. This demands for a materialization that is not only scalable, but also reactive to changes.
In this paper, we consider the problem of incremental materialization, that is, how to update the materialized derivations when new data is added or removed. To this purpose, we consider the ρdf RDFS fragment [12], and present a parallel system that implements a number of algorithms to quickly recalculate the derivation. In case new data is added, our system uses a parallel version of the well-known semi-naive evaluation of Datalog. In case of removals, we have implemented two algorithms, one based on previous theoretical work, and another one that is more efficient since it does not require a complete scan of the input.
We have evaluated the performance using a prototype system called DynamiTE, which organizes the knowledge bases with a number of indices to facilitate the query process and exploits parallelism to improve the performance. The results show that our methods are indeed capable to recalculate the derivation in a short time, opening the door to reasoning on much more dynamic data than is currently possible.
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References
Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley (1995), http://webdam.inria.fr/Alice/
Barbieri, D.F., Braga, D., Ceri, S., Della Valle, E., Grossniklaus, M.: Incremental Reasoning on Streams and Rich Background Knowledge. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010, Part I. LNCS, vol. 6088, pp. 1–15. Springer, Heidelberg (2010)
Broekstra, J., Kampman, A.: Inferencing and Truth Maintenance in RDF Schema: Exploring a Naive Practical Approach. In: Workshop on Practical and Scalable Semantic Systems (PSSS), Sanibel Island, Florida (2003)
Della Valle, E., Ceri, S., van Harmelen, F., Fensel, D.: It’s a streaming world! reasoning upon rapidly changing information. IEEE Intelligent Systems 24(6), 83–89 (2009)
Guo, Y., Pan, Z., Heflin, J.: LUBM: A benchmark for OWL knowledge base systems. Web Semantics: Science, Services and Agents on the World Wide Web 3, 158–182 (2005)
Gupta, A., Mumick, I.S.: Maintenance of Materialized Views: Problems, Techniques, and Applications. Data Engineering Bulletin 18(2), 3–18 (1995)
Gupta, A., Mumick, I.S., Subrahmanian, V.S.: Maintaining Views Incrementally. In: Proceedings of SIGMOD, vol. 22, pp. 157–166. ACM (1993)
Harrison, J.V., Dietrich, S.: Maintenance of Materialized Views in a Deductive Database: An update Propagation Approach. In: Workshop on Deductive Databases, JICSLP, pp. 56–65 (1992)
Hayes, P. (ed.): RDF Semantics. W3C Recommendation (2004)
Kolovski, V., Wu, Z., Eadon, G.: Optimizing Enterprise-scale OWL 2 RL Reasoning in a Relational Database System. 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. 436–452. Springer, Heidelberg (2010)
Kotowski, J., Bry, F., Brodt, S.: Reasoning as Axioms Change. In: Rudolph, S., Gutierrez, C. (eds.) RR 2011. LNCS, vol. 6902, pp. 139–154. Springer, Heidelberg (2011)
Munoz-Venegas, S., Prez, J., Gutierrez, C.: Simple and Efficient Minimal RDFS. Web Semantics: Science, Services and Agents on the World Wide Web 7(3) (2009)
Olson, M.A., Bostic, K., Seltzer, M.: Berkeley db. In: Proceedings of the FREENIX Track: 1999 USENIX Annual Technical Conference, pp. 183–192 (1999)
Prud’hommeaux, E., Seaborne, A.: SPARQL Query Language for RDF. W3C Recommendation (2008)
Staudt, M., Jarke, M.: Incremental Maintenance of Externally Materialized Views. In: Vijayaraman, T.M., Buchmann, A.P., Mohan, C., Sarda, N.L. (eds.) Proceedings of VLDB, pp. 75–86 (1996)
Urbani, J., Kotoulas, S., Maassen, J., Harmelen, F.V., Bal, H.: WebPIE: A Web-scale Parallel Inference Engine using MapReduce. Web Semantics: Science, Services and Agents on the World Wide Web 10, 59–75 (2012)
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)
Volz, R., Staab, S., Motik, B.: Incremental Maintenance of Materialized Ontologies. In: Meersman, R., Schmidt, D.C. (eds.) CoopIS 2003, DOA 2003, and ODBASE 2003. LNCS, vol. 2888, pp. 707–724. Springer, Heidelberg (2003)
Volz, R., Staab, S., Motik, B.: Incrementally maintaining materializations of ontologies stored in logic databases. In: Spaccapietra, S., Bertino, E., Jajodia, S., King, R., McLeod, D., Orlowska, M.E., Strous, L. (eds.) Journal on Data Semantics II. LNCS, vol. 3360, pp. 1–34. Springer, Heidelberg (2005)
Weaver, J., Hendler, J.A.: Parallel Materialization of the Finite RDFS Closure for Hundreds of Millions of Triples. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 682–697. Springer, Heidelberg (2009)
Weiss, C., Karras, P., Bernstein, A.: Hexastore: Sextuple indexing for semantic web data management. In: Proceedings of VLDB, vol. 1, pp. 1008–1019 (2008)
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Urbani, J., Margara, A., Jacobs, C., van Harmelen, F., Bal, H. (2013). DynamiTE: Parallel Materialization of Dynamic RDF Data. In: Alani, H., et al. The Semantic Web – ISWC 2013. ISWC 2013. Lecture Notes in Computer Science, vol 8218. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41335-3_41
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DOI: https://doi.org/10.1007/978-3-642-41335-3_41
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