Abstract
The need for reasoning over temporal data has recently emerged. DatalogMTL is a highly suitable language to handle many real-world applications. In spite of the deep theoretical contribution and the first experimental implementations of DatalogMTL, practical temporal reasoning applications call for a fully engineered system, able to reason with DatalogMTL while supporting a number of features of fundamental utility such as recursion, aggregation, and negation.
We introduce Temporal Vadalog, a new reasoning system for DatalogMTL that is capable of handling, among other elements, stratified negation and a form of aggregation. We evaluate the system in real-world and synthetic scenarios, comparatively showing its performance.
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Notes
- 1.
Our data structure is built around a hashmap, whose key is the fact and whose values are a collection of intervals. Currently, we use a tree-like structure as a collection that auto-merges adjacent intervals on insert.
References
The Temporal Vadalog System: Appendix. http://shorturl.at/biGR8
Alur, R., Henzinger, T.A.: Real-time logics: complexity and expressiveness. Inf. Comput. 104(1), 35–77 (1993)
Bellomarini, L., et al.: Reasoning on company takeovers during the COVID-19 crisis with knowledge graphs. In: RuleML+RR (Supplement), vol. 2644, pp. 145–156 (2020)
Bellomarini, L., Benedetto, D., Gottlob, G., Sallinger, E.: Vadalog: A modern architecture for automated reasoning with large knowledge graphs. Inf. Syst. 101528 (2020)
Bellomarini, L., Gottlob, G., Pieris, A., Sallinger, E.: Swift logic for big data and knowledge graphs. In: IJCAI (2017)
Bellomarini, L., Nissl, M., Sallinger, E.: Monotonic aggregation for temporal datalog. In: Proceedings of the 15th International Rule Challenge, vol. 2956 (2021)
Bellomarini, L., Nissl, M., Sallinger, E.: Query evaluation in DatalogMTL - taming infinite query results. CoRR abs/2109.10691 (2021)
Bellomarini, L., Nissl, M., Sallinger, E.: iTemporal: an extensible generator of temporal benchmarks. In: ICDE, pp. 2021–2033. IEEE (2022)
Bellomarini, L., Sallinger, E., Gottlob, G.: The Vadalog system: datalog-based reasoning for knowledge graphs. PVLDB 11(9), 975–987 (2018)
Bellomarini, L., Sallinger, E., Vahdati, S.: Knowledge graphs: the layered perspective. In: Janev, V., Graux, D., Jabeen, H., Sallinger, E. (eds.) Knowledge Graphs and Big Data Processing. LNCS, vol. 12072, pp. 20–34. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-53199-7_2
Bellomarini, L., Sallinger, E., Vahdati, S.: Reasoning in knowledge graphs: an embeddings spotlight. In: Janev, V., Graux, D., Jabeen, H., Sallinger, E. (eds.) Knowledge Graphs and Big Data Processing. LNCS, vol. 12072, pp. 87–101. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-53199-7_6
Brandt, S., Kalayci, E.G., Kontchakov, R., Ryzhikov, V., Xiao, G., Zakharyaschev, M.: Ontology-based data access with a horn fragment of metric temporal logic. In: AAAI, pp. 1070–1076. AAAI Press (2017)
Brandt, S., Kalayci, E.G., Ryzhikov, V., Xiao, G., Zakharyaschev, M.: Querying log data with metric temporal logic. J. Artif. Intell. Res. 62, 829–877 (2018)
Buschmann, F., Henney, K., Schmidt, D.C.: Pattern-Oriented Software Architecture, 4th edn. Wiley, Hoboken (2007)
Calì, A., Gottlob, G., Pieris, A.: New expressive languages for ontological query answering. In: Proceedings of AAAI, vol. 2011 (2011)
Ceri, S., Gottlob, G., Tanca, L.: What you always wanted to know about datalog (and never dared to ask). TKDE 1(1), 146–166 (1989)
Chomicki, J., Imielinski, T.: Temporal deductive databases and infinite objects. In: PODS, pp. 61–73 (1988)
Clarke, E.M., Emerson, E.A.: Design and synthesis of synchronization skeletons using branching time temporal logic. In: Kozen, D. (ed.) Logic of Programs 1981. LNCS, vol. 131, pp. 52–71. Springer, Heidelberg (1982). https://doi.org/10.1007/BFb0025774
Dalgliesh, J.: How the Enterprise Knowledge Graph Connects Oil and Gas Data Silos. Maana Blog (2016). https://shorturl.at/rsxU2
Garcia-Molina, H., Ullman, J.D., Widom, J.: Database Systems - The Complete Book, 2nd edn. Pearson Education, London (2009)
Gottlob, G., Pieris, A.: Beyond SPARQL under OWL 2 QL entailment regime: rules to the rescue. In: IJCAI, pp. 2999–3007 (2015)
Graefe, G., McKenna, W.J.: The volcano optimizer generator: extensibility and efficient search. In: ICDE, pp. 209–218 (1993)
He, Q., Chen, B.C., Agarwal, D.: Building The LinkedIn Knowledge Graph. LinkedIn Blog (2016). https://shorturl.at/aouyW
Koymans, R.: Specifying real-time properties with metric temporal logic. Real-Time Syst. 2(4), 255–299 (1990)
Leone, N., et al.: Enhancing DLV for large-scale reasoning. In: LPNMR, vol. 11481, pp. 312–325 (2019)
Leone, N., Manna, M., Terracina, G., Veltri, P.: Fast query answering over existential rules. ACM Trans. Comput. Log. 20(2), 12:1–12:48 (2019)
Maier, D., Mendelzon, A.O., Sagiv, Y.: Testing implications of data dependencies. ACM Trans. Database Syst. 4(4), 455–468 (1979)
Pnueli, A.: The temporal logic of programs. In: 18th Annual Symposium on Foundations of Computer Science (SFCS 1977), pp. 46–57 (1977)
Sciore, E.: Database Design and Implementation, 2nd edn. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-33836-7
Tena Cucala, D.J., Walega, P.A., Cuenca Grau, B., Kostylev, E.V.: Stratified negation in datalog with metric temporal operators. In: AAAI, pp. 6488–6495 (2021)
Walega, P.A., Cuenca Grau, B., Kaminski, M., Kostylev, E.V.: Datalogmtl: computational complexity and expressive power. In: IJCAI, pp. 1886–1892 (2019)
Walega, P.A., Cuenca Grau, B., Kaminski, M., Kostylev, E.V.: Datalogmtl over the integer timeline. In: KR, pp. 768–777 (2020)
Walega, P.A., Cuenca Grau, B., Kaminski, M., Kostylev, E.V.: Tractable fragments of datalog with metric temporal operators. In: IJCAI, pp. 1919–1925 (2020)
Walega, P.A., Kaminski, M., Cuenca Grau, B.: Reasoning over streaming data in metric temporal datalog. In: AAAI, pp. 3092–3099 (2019)
Wang, D., Hu, P., Walega, P., Cuenca Grau, B.: Meteor: practical reasoning in datalog with metric temporal operators. In: Proceedings of AAAI-2022 (2022)
Acknowledgements
This work was supported by the Vienna Science and Technology Fund (WWTF) grant VRG18-013, and the “rAIson data” Royal Society grant of Prof. Georg Gottlob.
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Bellomarini, L., Blasi, L., Nissl, M., Sallinger, E. (2022). The Temporal Vadalog System. In: Governatori, G., Turhan, AY. (eds) Rules and Reasoning. RuleML+RR 2022. Lecture Notes in Computer Science, vol 13752. Springer, Cham. https://doi.org/10.1007/978-3-031-21541-4_9
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