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Querying log data with metric temporal logic

Published: 01 May 2018 Publication History

Abstract

We propose a novel framework for ontology-based access to temporal log data using a datalog extension datalogMTL of the Horn fragment of the metric temporal logic MTL. We show that datalogMTL is EXPSPACE-complete even with punctual intervals, in which case full MTL is known to be undecidable. We also prove that nonrecursive datalogMTL is PSPACE-complete for combined complexity and in AC0 for data complexity. We demonstrate by two real-world use cases that nonrecursive datalogMTL programs can express complex temporal concepts from typical user queries and thereby facilitate access to temporal log data. Our experiments with Siemens turbine data and MesoWest weather data show that datalogMTL ontology-mediated queries are efficient and scale on large datasets.

References

[1]
Abiteboul, S., Hull, R., & Vianu, V. (1995). Foundations of Databases. Addison-Wesley.
[2]
Alur, R., Feder, T., & Henzinger, T. A. (1996). The benefits of relaxing punctuality. J. ACM, 43(1), 116-146.
[3]
Alur, R., & Henzinger, T. A. (1993). Real-time logics: Complexity and expressiveness. Inf. Comput., 104(1), 35-77.
[4]
Armbrust, M., Xin, R. S., Lian, C., Huai, Y., Liu, D., Bradley, J. K., Meng, X., Kaftan, T., Franklin, M. J., Ghodsi, A., & Zaharia, M. (2015). Spark SQL: relational data processing in spark. In Sellis, T. K., Davidson, S. B., & Ives, Z. G. (Eds.), Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31 - June 4, 2015, pp. 1383-1394. ACM.
[5]
Arora, S., & Barak, B. (2009). Computational Complexity: A Modern Approach (1st edition). Cambridge University Press, New York, USA.
[6]
Artale, A., Kontchakov, R., Wolter, F., & Zakharyaschev, M. (2013). Temporal description logic for ontology-based data access. In Proc. of the 23rd Int. Joint Conf. on Artificial Intelligence, IJCAI 2013. IJCAI/AAAI.
[7]
Artale, A., Kontchakov, R., Kovtunova, A., Ryzhikov, V., Wolter, F., & Zakharyaschev, M. (2015). First-order rewritability of temporal ontology-mediated queries. In Proc. of the 24th Int. Joint Conf. on Artificial Intelligence, IJCAI 2015, pp. 2706-2712. IJCAI/AAAI.
[8]
Artale, A., Kontchakov, R., Kovtunova, A., Ryzhikov, V., Wolter, F., & Zakharyaschev, M. (2017). Ontology-mediated query answering over temporal data: A survey (invited talk). In TIME, Vol. 90 of LIPIcs, pp. 1:1-1:37. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik.
[9]
Artale, A., Kontchakov, R., Ryzhikov, V., & Zakharyaschev, M. (2013). The complexity of clausal fragments of LTL. In Logic for Programming, Artificial Intelligence, and Reasoning - 19th International Conference, LPAR-19, Stellenbosch, South Africa, December 14-19, 2013. Proceedings, pp. 35-52.
[10]
Artale, A., Kontchakov, R., Ryzhikov, V., & Zakharyaschev, M. (2014). A cookbook for temporal conceptual data modelling with description logics. ACM Trans. Comput. Log., 15(3), 25:1- 25:50.
[11]
Baader, F., Borgwardt, S., & Lippmann, M. (2013). Temporalizing ontology-based data access. In Proc. of the 24th Int. Conf. on Automated Deduction, CADE-24, Vol. 7898 of LNCS, pp. 330-344. Springer.
[12]
Baudinet, M., Chomicki, J., & Wolper, P. (1993). Temporal deductive databases. In Temporal Databases, pp. 294-320.
[13]
Beck, H., Dao-Tran, M., Eiter, T., & Fink, M. (2015). LARS: A logic-based framework for analyzing reasoning over streams. In Bonet, B., & Koenig, S. (Eds.), Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 25-30, 2015, Austin, Texas, USA., pp. 1431-1438. AAAI Press.
[14]
Bienvenu, M., Kikot, S., Kontchakov, R., Podolskii, V. V., & Zakharyaschev, M. (2018). Ontology-mediated queries: Combined complexity and succinctness of rewritings via circuit complexity. J. ACM. In print.
[15]
Borgwardt, S., Lippmann, M., & Thost, V. (2013). Temporal query answering in the description logic DL-Lite. In Proc. of the 9th Int. Symposium on Frontiers of Combining Systems, FroCoS'13, Vol. 8152 of LNCS, pp. 165-180. Springer.
[16]
Brandt, S., Kalayci, E. G., Kontchakov, R., Ryzhikov, V., Xiao, G., & Zakharyaschev, M. (2017). Ontology-based data access with a horn fragment of metric temporal logic. In Singh, S. P., & Markovitch, S. (Eds.), Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA., pp. 1070-1076. AAAI Press.
[17]
Bresolin, D., Kurucz, A., Muñoz-Velasco, E., Ryzhikov, V., Sciavicco, G., & Zakharyaschev, M. (2017). Horn fragments of the halpern-shoham interval temporal logic. ACM Trans. Comput. Log., 18(3), 22:1-22:39.
[18]
Calvanese, D., Cogrel, B., Komla-Ebri, S., Kontchakov, R., Lanti, D., Rezk, M., Rodriguez-Muro, M., & Xiao, G. (2017). Ontop: Answering SPARQL queries over relational databases. Semantic Web, 8(3), 471-487.
[19]
Chomicki, J., & Toman, D. (1998). Temporal logic in information systems. In Logics for Databases and Information Systems, pp. 31-70. Kluwer.
[20]
Furia, C. A., & Spoletini, P. (2008). Tomorrow and all our yesterdays: MTL satisfiability over the integers. In Fitzgerald, J. S., Haxthausen, A. E., & Yenigün, H. (Eds.), Theoretical Aspects of Computing - ICTAC 2008, 5th International Colloquium, Istanbul, Turkey, September 1-3, 2008. Proceedings, Vol. 5160 of Lecture Notes in Computer Science, pp. 126-140. Springer.
[21]
Gabbay, D., Kurucz, A., Wolter, F., & Zakharyaschev, M. (2003). Many-Dimensional Modal Logics: Theory and Applications, Vol. 148 of Studies in Logic and the Foundations of Mathematics. Elsevier.
[22]
Gottlob, G., Kikot, S., Kontchakov, R., Podolskii, V. V., Schwentick, T., & Zakharyaschev, M. (2014). The price of query rewriting in ontology-based data access. Artif. Intell., 213, 42-59.
[23]
Gutiérrez-Basulto, V., Jung, J., & Kontchakov, R. (2016a). Temporalized EL ontologies for accessing temporal data: Complexity of atomic queries. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16). AAAI Press.
[24]
Gutiérrez-Basulto, V., Jung, J. C., & Ozaki, A. (2016b). On metric temporal description logics. In ECAI, Vol. 285 of Frontiers in Artificial Intelligence and Applications, pp. 837-845. IOS Press.
[25]
Gutiérrez-Basulto, V., & Klarman, S. (2012). Towards a unifying approach to representing and querying temporal data in description logics. In Proc. of the 6th Int. Conf. on Web Reasoning and Rule Systems, RR 2012, Vol. 7497 of LNCS, pp. 90-105. Springer.
[26]
Kharlamov, E., Brandt, S., Jiménez-Ruiz, E., Kotidis, Y., Lamparter, S., Mailis, T., Neuenstadt, C., Özçep, Ö. L., Pinkel, C., Svingos, C., Zheleznyakov, D., Horrocks, I., Ioannidis, Y. E., & Möller, R. (2016). Ontology-based integration of streaming and static relational data with optique. In Proc. of the 2016 Int. Conf. on Management of Data, SIGMOD Conference 2016, pp. 2109-2112.
[27]
Kharlamov, E., Mailis, T., Mehdi, G., Neuenstadt, C., Özçep, Ö. L., Roshchin, M., Solomakhina, N., Soylu, A., Svingos, C., Brandt, S., Giese, M., Ioannidis, Y. E., Lamparter, S., Möller, R., Kotidis, Y., & Waaler, A. (2017). Semantic access to streaming and static data at siemens. J. Web Sem., 44, 54-74.
[28]
Klarman, S., & Meyer, T. (2014). Querying temporal databases via OWL 2 QL. In Proc. of the 8th Int. Conf. on Web Reasoning and Rule Systems, RR 2014, Vol. 8741 of LNCS, pp. 92-107. Springer.
[29]
Kontchakov, R., Rezk, M., Rodriguez-Muro, M., Xiao, G., & Zakharyaschev, M. (2014). Answering SPARQL queries over databases under OWL 2 QL entailment regime. In Proc. of the 13th Int. Semantic Web Conf. (ISWC 2014), Part I, Vol. 8796 of LNCS, pp. 552-567. Springer.
[30]
Kontchakov, R., Pandolfo, L., Pulina, L., Ryzhikov, V., & Zakharyaschev, M. (2016). Temporal and spatial OBDA with many-dimensional halpern-shoham logic. In IJCAI, pp. 1160-1166. IJCAI/AAAI Press.
[31]
Koymans, R. (1990). Specifying real-time properties with metric temporal logic. Real-Time Systems, 2(4), 255-299.
[32]
Ladner, R. E. (1977). The computational complexity of provability in systems of modal propositional logic. SIAM Journal of Computing.
[33]
Lutz, C., Wolter, F., & Zakharyaschev, M. (2008). Temporal description logics: A survey. In Proc. of the 15th Int. Symposium on Temporal Representation and Reasoning (TIME 2008), pp. 3-14.
[34]
Madnani, K., Krishna, S. N., & Pandya, P. K. (2013). On the decidability and complexity of some fragments of Metric Temporal Logic. CoRR, abs/1305.6137.
[35]
Ouaknine, J., & Worrell, J. (2005). On the decidability of metric temporal logic. In Proceedings of the 20th Annual IEEE Symposium on Logic in Computer Science, LICS '05, pp. 188-197, Washington, DC, USA. IEEE Computer Society.
[36]
Ouaknine, J., & Worrell, J. (2008). Some recent results in metric temporal logic. In Formal Modeling and Analysis of Timed Systems, 6th International Conference, FORMATS 2008, Saint Malo, France, September 15-17, 2008. Proceedings, pp. 1-13.
[37]
Özçep, Ö., Möller, R., Neuenstadt, C., Zheleznyakov, D., & Kharlamov, E. (2013). A semantics for temporal and stream-based query answering in an OBDA context. Tech. rep., Deliverable D5.1, FP7-318338, EU.
[38]
Özçep, Ö. L., & Möller, R. (2014). Ontology based data access on temporal and streaming data. In the 10th Int. Summer School on Reasoning Web, RW 2014, Vol. 8714 of LNCS, pp. 279-312. Springer.
[39]
Poggi, A., Lembo, D., Calvanese, D., De Giacomo, G., Lenzerini, M., & Rosati, R. (2008). Linking data to ontologies. J. on Data Semantics, X, 133-173.
[40]
PostgreSQL (2018). Documentation 9.6.10. https://www.postgresql.org/docs/9.6/static/parallel-safety.html.
[41]
Raheb, K. E., Mailis, T., Ryzhikov, V., Papapetrou, N., & Ioannidis, Y. E. (2017). Balonse: Temporal aspects of dance movement and its ontological representation. In ESWC (2), Vol. 10250 of Lecture Notes in Computer Science, pp. 49-64.
[42]
Rodriguez-Muro, M., Kontchakov, R., & Zakharyaschev, M. (2013). Ontology-based data access: Ontop of databases. In The Semantic Web - ISWC 2013 - 12th International Semantic Web Conference, Sydney, NSW, Australia, October 21-25, 2013, Proceedings, Part I, pp. 558-573.
[43]
Sistla, A., & Clarke, E. (1985). The complexity of propositional linear temporal logics. J. ACM, 32, 733-749.
[44]
Soylu, A., Giese, M., Jiménez-Ruiz, E., Vega-Gorgojo, G., & Horrocks, I. (2016). Experiencing OptiqueVQS: a multi-paradigm and ontology-based visual query system for end users. Universal Access in the Information Society, 15(1), 129-152.
[45]
Tobies, S. (2001). Pspace reasoning for graded modal logics. Journal of Logic and Computation, 11(1), 85-106.
[46]
Ullman, J. D. (1988). Principles of Database and Knowledge-Base Systems, Volume I. Computer Science Press.
[47]
Vardi, M. (1982). The complexity of relational query languages (extended abstract). In Proc. of the 14th ACM SIGACT Symp. on Theory of Computing (STOC'82), pp. 137-146.
[48]
Xiao, G., Calvanese, D., Kontchakov, R., Lembo, D., Poggi, A., Rosati, R., & Zakharyaschev, M. (2018). Ontology-based data access: A survey. In Proc. of the 28th Int. Joint Conf. on Artificial Intelligence (IJCAI). IJCAI/AAAI.
[49]
Zaharia, M., Xin, R. S., Wendell, P., Das, T., Armbrust, M., Dave, A., Meng, X., Rosen, J., Venkataraman, S., Franklin, M. J., Ghodsi, A., Gonzalez, J., Shenker, S., & Stoica, I. (2016). Apache spark: a unified engine for big data processing. Commun. ACM, 59(11), 56-65.
[50]
Zhou, X., Wang, F., & Zaniolo, C. (2006). Efficient temporal coalescing query support in relational database systems. In Proc. of the 17th Int. Conf. on Database and Expert Systems Applications, DEXA 2006, Vol. 4080 of LNCS, pp. 676-686. Springer.

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    cover image Journal of Artificial Intelligence Research
    Journal of Artificial Intelligence Research  Volume 62, Issue 1
    May 2018
    871 pages
    ISSN:1076-9757
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    AI Access Foundation

    El Segundo, CA, United States

    Publication History

    Published: 01 May 2018
    Published in JAIR Volume 62, Issue 1

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