Skip to main content
SpringerLink
Log in

On Combining Ontologies and Rules

  • Chapter
  • First Online:
Reasoning Web. Declarative Artificial Intelligence (Reasoning Web 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13100))

Included in the following conference series:

  • 480 Accesses

Abstract

Ontology languages, based on Description Logics, and nonmonotonic rule languages are two major formalisms for the representation of expressive knowledge and reasoning with it, that build on fundamentally different ideas and formal underpinnings. Within the Semantic Web initiative, driven by the World Wide Web Consortium, standardized languages for these formalisms have been developed that allow their usage in knowledge-intensive applications integrating increasing amounts of data on the Web. Often, such applications require the advantages of both these formalisms, but due to their inherent differences, the integration is a challenging task. In this course, we review the two formalisms and their characteristics and show different ways of achieving their integration. We also discuss an available tool based on one such integration with favorable properties, such as polynomial data complexity for query answering when standard inference is polynomial in the used ontology language.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    http://www.w3.org.

  2. 2.

    https://lod-cloud.net/.

  3. 3.

    http://www.ihtsdo.org/snomed-ct/.

  4. 4.

    Please note that often also function symbols are introduced in the literature of LP, but since they jeopardize decidability of reasoning, and usually are not considered in integrations of ontologies and nonmonotonic rules, we do omit them here.

  5. 5.

    This is adapted from https://hts.usitc.gov/.

  6. 6.

    Classical negation is also allowed, but we simplify here for the sake of presentation.

  7. 7.

    http://nohr.di.fct.unl.pt.

  8. 8.

    The source code can be obtained at https://github.com/NoHRReasoner/NoHR.

  9. 9.

    http://protege.stanford.edu.

  10. 10.

    http://xsb.sourceforge.net.

  11. 11.

    Similar concepts have been used before for adding database support to rule systems, such as \(DLV^{DB}\) [78], and in ontology based data access, such as in ontop [19].

  12. 12.

    http://interprolog.com/java-bridge/.

References

  1. Alberti, M., Knorr, M., Gomes, A.S., Leite, J., Gonçalves, R., Slota, M.: Normative systems require hybrid knowledge bases. In: van der Hoek, W., Padgham, L., Conitzer, V., Winikoff, M. (eds.) Proceedings of AAMAS, pp. 1425–1426. IFAAMAS (2012)

    Google Scholar 

  2. Alferes, J.J., Knorr, M., Swift, T.: Query-driven procedures for hybrid MKNF knowledge bases. ACM Trans. Comput. Log. 14(2), 1–43 (2013)

    MATH  Google Scholar 

  3. Alviano, M., et al.: The ASP system DLV2. In: Balduccini, M., Janhunen, T. (eds.) LPNMR 2017. LNCS (LNAI), vol. 10377, pp. 215–221. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61660-5_19

    Chapter  Google Scholar 

  4. Artale, A., Calvanese, D., Kontchakov, R., Zakharyaschev, M.: The \(DL\)-\(Lite\) family and relations. J. Artif. Intell. Res. (JAIR) 36, 1–69 (2009)

    MATH  Google Scholar 

  5. Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation, and Applications, 3rd edn. Cambridge University Press, Cambridge (2010)

    MATH  Google Scholar 

  6. Baader, F., Brandt, S., Lutz, C.: Pushing the \(\cal{EL}\) envelope. In: Kaelbling, L.P., Saffiotti, A. (eds.) Proceedings of IJCAI, pp. 364–369. Professional Book Center (2005)

    Google Scholar 

  7. Baader, F., Hollunder, B.: Embedding defaults into terminological representation systems. J. Autom. Reason. 14, 149–180 (1995)

    MATH  Google Scholar 

  8. Baget, J., Leclère, M., Mugnier, M., Salvat, E.: On rules with existential variables: Walking the decidability line. Artif. Intell. 175(9–10), 1620–1654 (2011)

    MATH  Google Scholar 

  9. Bajraktari, L., Ortiz, M., Simkus, M.: Combining rules and ontologies into clopen knowledge bases. In: McIlraith, S.A., Weinberger, K.Q. (eds.) Proceedings of AAAI, pp. 1728–1735. AAAI Press (2018)

    Google Scholar 

  10. Baral, C., Gelfond, M.: Logic programming and knowledge representation. J. Log. Program. 19(20), 73–148 (1994)

    MATH  Google Scholar 

  11. Beck, H., Dao-Tran, M., Eiter, T.: LARS: a logic-based framework for analytic reasoning over streams. Artif. Intell. 261, 16–70 (2018)

    MATH  Google Scholar 

  12. Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American, pp. 96–101, May 2001

    Google Scholar 

  13. Bonatti, P.A., Lutz, C., Wolter, F.: The complexity of circumscription in DLs. J. Artif. Intell. Res. (JAIR) 35, 717–773 (2009)

    MATH  Google Scholar 

  14. Brachman, R.J., Levesque, H.J.: Knowledge Representation and Reasoning. Elsevier, Amsterdam (2004)

    MATH  Google Scholar 

  15. Brewka, G., Ellmauthaler, S., Gonçalves, R., Knorr, M., Leite, J., Pührer, J.: Reactive multi-context systems: heterogeneous reasoning in dynamic environments. Artif. Intell. 256, 68–104 (2018)

    MATH  Google Scholar 

  16. Britz, K., Casini, G., Meyer, T., Moodley, K., Sattler, U., Varzinczak, I.: Principles of KLM-style defeasible description logics. ACM Trans. Comput. Log. 22(1), 1:1-1:46 (2021)

    Google Scholar 

  17. Calì, A., Gottlob, G., Lukasiewicz, T., Pieris, A.: Datalog+/-: a family of languages for ontology querying. In: de Moor, O., Gottlob, G., Furche, T., Sellers, A. (eds.) Datalog 2.0 2010. LNCS, vol. 6702, pp. 351–368. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-24206-9_20

    Chapter  Google Scholar 

  18. Calimeri, F., et al.: Asp-core-2 input language format. Theory Pract. Log. Program. 20(2), 294–309 (2020)

    MATH  Google Scholar 

  19. Calvanese, D., Cogrel, B., Komla-Ebri, S., Kontchakov, R., Lanti, D., Rezk, M., Rodriguez-Muro, M., Xiao, G.: Ontop: answering SPARQL queries over relational databases. Semantic Web 8(3), 471–487 (2017)

    Google Scholar 

  20. Chen, W., Warren, D.S.: Tabled evaluation with delaying for general logic programs. J. ACM 43(1), 20–74 (1996)

    MATH  Google Scholar 

  21. Costa, N., Knorr, M., Leite, J.: Next step for NoHR: OWL 2 QL. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9366, pp. 569–586. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25007-6_33

    Chapter  Google Scholar 

  22. Dao-Tran, M., Eiter, T.: Streaming multi-context systems. In: IJCAI, pp. 1000–1007. ijcai.org (2017)

    Google Scholar 

  23. Donini, F.M., Nardi, D., Rosati, R.: Description logics of minimal knowledge and negation as failure. ACM Trans. Comput. Logic 3(2), 177–225 (2002)

    MATH  Google Scholar 

  24. Eiter, T., Fink, M., Ianni, G., Krennwallner, T., Redl, C., Schüller, P.: A model building framework for answer set programming with external computations. TPLP 16(4), 418–464 (2016)

    MATH  Google Scholar 

  25. Eiter, T., Ianni, G., Krennwallner, T., Polleres, A.: Rules and ontologies for the semantic web. In: Baroglio, C., et al. (eds.) Reasoning Web. LNCS, vol. 5224, pp. 1–53. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85658-0_1

    Chapter  Google Scholar 

  26. Eiter, T., Ianni, G., Lukasiewicz, T., Schindlauer, R.: Well-founded semantics for description logic programs in the semantic web. ACM Trans. Comput. Logic. 12, 11:1-11:41 (2011)

    MATH  Google Scholar 

  27. Eiter, T., Ianni, G., Lukasiewicz, T., Schindlauer, R., Tompits, H.: Combining answer set programming with description logics for the semantic web. Artif. Intell. 172(12–13), 1495–1539 (2008)

    MATH  Google Scholar 

  28. Eiter, T., Šimkus, M.: Linking open-world knowledge bases using nonmonotonic rules. In: Calimeri, F., Ianni, G., Truszczynski, M. (eds.) LPNMR 2015. LNCS (LNAI), vol. 9345, pp. 294–308. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23264-5_25

    Chapter  MATH  Google Scholar 

  29. Gebser, M., Kaufmann, B., Kaminski, R., Ostrowski, M., Schaub, T., Schneider, M.: Potassco: the potsdam answer set solving collection. AI Commun. 24(2), 107–124 (2011)

    MATH  Google Scholar 

  30. van Gelder, A.: The alternating fixpoint of logic programs with negation. In: Principles of Database Systems, pp. 1–10. ACM Press (1989)

    Google Scholar 

  31. van Gelder, A., Ross, K.A., Schlipf, J.S.: The well-founded semantics for general logic programs. J. ACM 38(3), 620–650 (1991)

    MATH  Google Scholar 

  32. Gelfond, M., Lifschitz, V.: Classical negation in logic programs and disjunctive databases. New Gener. Comput. 9, 365–385 (1991)

    MATH  Google Scholar 

  33. Giordano, L., Gliozzi, V., Olivetti, N., Pozzato, G.L.: Semantic characterization of rational closure: from propositional logic to description logics. Artif. Intell. 226, 1–33 (2015)

    MATH  Google Scholar 

  34. Glimm, B., Horrocks, I., Motik, B., Stoilos, G., Wang, Z.: Hermit: an OWL 2 reasoner. J. Autom. Reason. 53(3), 245–269 (2014)

    MATH  Google Scholar 

  35. Gottlob, G., Hernich, A., Kupke, C., Lukasiewicz, T.: Equality-friendly well-founded semantics and applications to description logics. In: AAAI. AAAI Press (2012)

    Google Scholar 

  36. Grosof, B.N., Horrocks, I., Volz, R., Decker, S.: Description logic programs: combining logic programs with description logic. In: Hencsey, G., White, B., Chen, Y.R., Kovács, L., Lawrence, S. (eds.) Proceedings of WWW, pp. 48–57. ACM (2003)

    Google Scholar 

  37. Haarslev, V., Hidde, K., Möller, R., Wessel, M.: The RacerPro knowledge representation and reasoning system. Seman. Web J. (2011). http://www.semantic-web-journal.net/issues. (to appear)

  38. Harris, S., Seaborne, A. (eds.): SPARQL 1.1 Query Language. W3C Working Group Note 21 March 2013 (2013). https://www.w3.org/TR/sparql11-query/

  39. Hitzler, P.: A review of the semantic web field. Commun. ACM 64(2), 76–83 (2021)

    Google Scholar 

  40. Hitzler, P., Krötzsch, M., Parsia, B., Patel-Schneider, P.F., Rudolph, S. (eds.): OWL 2 Web Ontology Language: Primer (Second Edition). W3C, Cambridge(2012)

    Google Scholar 

  41. Hitzler, P., Krötzsch, M., Rudolph, S.: Foundations of Semantic Web Technologies. Chapman & Hall/CRC, Boca Raton (2009)

    Google Scholar 

  42. Horrocks, I., Kutz, O., Sattler, U.: The even more irresistible \(\cal{SROIQ}\). In: Doherty, P., Mylopoulos, J., Welty, C.A. (eds.) Proceedings of KR, pp. 57–67. AAAI Press (2006)

    Google Scholar 

  43. Ivanov, V., Knorr, M., Leite, J.: A query tool for \(\cal{EL}\) with Non-monotonic Rules. In: Alani, J., et al. (eds.) ISWC 2013. LNCS, vol. 8218, pp. 216–231. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41335-3_14

    Chapter  Google Scholar 

  44. Kaminski, T., Knorr, M., Leite, J.: Efficient paraconsistent reasoning with ontologies and rules. In: Yang, Q., Wooldridge, M.J. (eds.) Proceedings of IJCAI, pp. 3098–3105. AAAI Press (2015)

    Google Scholar 

  45. Kasalica, V., Gerochristos, I., Alferes, J.J., Gomes, A.S., Knorr, M., Leite, J.: Telco network inventory validation with nohr. In: Balduccini, M., Lierler, Y., Woltran, S. (eds.) Logic Programming and Nonmonotonic Reasoning. LPNMR 2019. Lecture Notes in Computer Science, 11481, pp. 18–331. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-20528-7_2

  46. Kazakov, Y.: \(\cal{RIQ}\) and \(\cal{SROIQ}\) are harder than \(\cal{SHOIQ}\). In: Brewka, G., Lang, J. (eds.) Principles of Knowledge Representation and Reasoning: Proceedings of the Eleventh International Conference, KR 2008, Sydney, Australia, September 16–19, 2008. AAAI Press (2008)

    Google Scholar 

  47. Kazakov, Y., Krötzsch, M., Simančík, F.: The incredible ELK: from polynomial procedures to efficient reasoning with \(\cal{EL}\) ontologies. J. Autom. Reason. 53, 1–61 (2013)

    MATH  Google Scholar 

  48. Knorr, M., Alferes, J.J., Hitzler, P.: Local closed world reasoning with description logics under the well-founded semantics. Artif. Intell. 175(9–10), 1528–1554 (2011)

    MATH  Google Scholar 

  49. Knorr, M., Hitzler, P., Maier, F.: Reconciling OWL and non-monotonic rules for the semantic web. In: Raedt, L.D., Bessiere, C., Dubois, D., Doherty, P., Frasconi, P., Heintz, F., Lucas, P.J.F. (eds.) Proceedings of ECAI. Frontiers in Artificial Intelligence and Applications, vol. 242, pp. 474–479. IOS Press (2012)

    Google Scholar 

  50. Krisnadhi, A.A., Maier, F., Hitzler, P.: OWL and rules. In: Reasoning Web 2011, Springer Lecture Notes in Computer Science (2011). http://knoesis.wright.edu/faculty/pascal/resources/publications/OWL-Rules-2011.pdf (to appear)

  51. Krisnadhi, A.A., Sengupta, K., Hitzler, P.: Local closed world semantics: Keep it simple, stupid! Technical report, Wright State University (2011). http://pascal-hitzler.de/resources/publications/GC-DLs.pdf

  52. Lehmann, J., Isele, R., Jakob, M., Jentzsch, A., Kontokostas, D., Mendes, P.N., Hellmann, S., Morsey, M., van Kleef, P., Auer, S., Bizer, C.: Dbpedia - a large-scale, multilingual knowledge base extracted from Wikipedia. Semantic Web 6(2), 167–195 (2015)

    Google Scholar 

  53. Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S., Scarcello, F.: The DLV system for knowledge representation and reasoning. ACM Trans. Comput. Logic 7, 499–562 (2006)

    MATH  Google Scholar 

  54. Lifschitz, V.: Nonmonotonic databases and epistemic queries. In: Mylopoulos, J., Reiter, R. (eds.) Proceedings of IJCAI. Morgan Kaufmann (1991)

    Google Scholar 

  55. Lopes, C., Knorr, M., Leite, J.: NoHR: integrating XSB Prolog with the OWL 2 profiles and beyond. In: Balduccini, M., Janhunen, T. (eds.) LPNMR 2017. LNCS (LNAI), vol. 10377, pp. 236–249. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61660-5_22

    Chapter  MATH  Google Scholar 

  56. Lukumbuzya, S., Ortiz, M., Simkus, M.: Resilient logic programs: answer set programs challenged by ontologies. In: AAAI, pp. 2917–2924. AAAI Press (2020)

    Google Scholar 

  57. Lutz, C.: The complexity of conjunctive query answering in expressive description logics. In: Armando, A., Baumgartner, P., Dowek, G. (eds.) IJCAR 2008. LNCS (LNAI), vol. 5195, pp. 179–193. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-71070-7_16

    Chapter  Google Scholar 

  58. Magka, D., Krötzsch, M., Horrocks, I.: Computing stable models for nonmonotonic existential rules. In: IJCAI, pp. 1031–1038. IJCAI/AAAI (2013)

    Google Scholar 

  59. Minker, J., Seipel, D.: Disjunctive logic programming: a survey and assessment. In: Kakas, A.C., Sadri, F. (eds.) Computational Logic: Logic Programming and Beyond. LNCS (LNAI), vol. 2407, pp. 472–511. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45628-7_18

    Chapter  MATH  Google Scholar 

  60. Morgenstern, L., Welty, C., Boley, H., Hallmark, G. (eds.): RIF Primer (Second Edition). W3C Working Group Note 5 February 2013 (2013). https://www.w3.org/TR/2014/NOTE-rdf11-primer-20140624/

  61. Motik, B., Cuenca Grau, B., Horrocks, I., Wu, Z., Fokoue, A., Lutz, C. (eds.): OWL 2 Web Ontology Language: Profiles (Second Edition). W3C, Cambridge (2012)

    Google Scholar 

  62. Motik, B., Rosati, R.: Reconciling description logics and rules. J. ACM 57(5), 93–154 (2010)

    MATH  Google Scholar 

  63. Motik, B., Sattler, U., Studer, R.: Query-answering for OWL-DL with rules. J. Web Semant. 3(1), 41–60 (2005)

    Google Scholar 

  64. Nenov, Y., Piro, R., Motik, B., Horrocks, I., Wu, Z., Banerjee, J.: RDFox: a highly-scalable RDF store. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9367, pp. 3–20. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25010-6_1

    Chapter  Google Scholar 

  65. Patel, C., et al.: Matching patient records to clinical trials using ontologies. In: Aberer, K., et al. (eds.) ASWC/ISWC -2007. LNCS, vol. 4825, pp. 816–829. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-76298-0_59

    Chapter  Google Scholar 

  66. Redl, C.: The DLVHEX system for knowledge representation: recent advances (system description). Theory Pract. Log. Program. 16(5–6), 866–883 (2016)

    MATH  Google Scholar 

  67. Rosati, R.: On the decidability and complexity of integrating ontologies and rules. J. Web Semant. 3(1), 41–60 (2005)

    Google Scholar 

  68. Rosati, R.: DL+Log: A tight integration of description logics and disjunctive datalog. In: Doherty, P., Mylopoulos, J., Welty, C. (eds.) Tenth International Conference on the Principles of Knowledge Representation and Reasoning, KR 2006, pp. 68–78. AAAI Press (2006)

    Google Scholar 

  69. Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach, 4th edn. Pearson, London (2020)

    MATH  Google Scholar 

  70. Schreiber, G., Raimond, Y. (eds.): RDF 1.1 Primer. W3C Working Group Note 24 June 2014 (2014). available at https://www.w3.org/TR/2014/NOTE-rdf11-primer-20140624/

  71. Sirin, E., Parsia, B., Grau, B.C., Kalyanpur, A., Katz, Y.: Pellet: a practical OWL-DL reasoner. Web Semant. 5, 51–53 (2007)

    Google Scholar 

  72. Slota, M., Leite, J.: Towards closed world reasoning in dynamic open worlds. TPLP 10(4–6), 547–563 (2010)

    MATH  Google Scholar 

  73. Slota, M., Leite, J., Swift, T.: Splitting and updating hybrid knowledge bases. TPLP 11(4–5), 801–819 (2011)

    MATH  Google Scholar 

  74. Slota, M., Leite, J., Swift, T.: On updates of hybrid knowledge bases composed of ontologies and rules. Artif. Intell. 229, 33–104 (2015)

    MATH  Google Scholar 

  75. Steigmiller, A., Liebig, T., Glimm, B.: Konclude: system description. J. Web Sem. 27, 78–85 (2014)

    MATH  Google Scholar 

  76. Sterling, L., Shapiro, E.: The Art of Prolog - Advanced Programming Techniques, 2nd edn. MIT Press, Cambridge (1994)

    MATH  Google Scholar 

  77. Swift, T., Warren, D.S.: XSB: extending prolog with tabled logic programming. Theory Pract. Log. Program. 12(1–2), 157–187 (2012)

    MATH  Google Scholar 

  78. Terracina, G., Leone, N., Lio, V., Panetta, C.: Experimenting with recursive queries in database and logic programming systems. TPLP 8(2), 129–165 (2008)

    MATH  Google Scholar 

  79. Tsarkov, D., Horrocks, I.: FaCT++ description logic reasoner: system description. In: Furbach, U., Shankar, N. (eds.) IJCAR 2006. LNCS (LNAI), vol. 4130, pp. 292–297. Springer, Heidelberg (2006). https://doi.org/10.1007/11814771_26

    Chapter  Google Scholar 

  80. Wang, Y., You, J.H., Yuan, L.Y., Shen, Y.D.: Loop formulas for description logic programs. Theory Pract. Logic Program. 10(4–6), 531–545 (2010)

    MATH  Google Scholar 

  81. Xiao, G., et al.: Ontology-based data access: a survey. In: IJCAI, pp. 5511–5519. ijcai.org (2018)

    Google Scholar 

Download references

Acknowledgement

The author thanks Ricardo Gonçalves and the anonymous reviewers for helpful feedback and acknowledges partial support by FCT projects RIVER (PTDC/CCI-COM/30952/2017) and NOVA LINCS (UIDB/04516/2020).

Author information

Authors and Affiliations

  1. Universidade Nova de Lisboa, Caparica, Portugal

    Matthias Knorr

Authors
  1. Matthias Knorr
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthias Knorr .

Editor information

Editors and Affiliations

  1. TU Wien, Vienna, Austria

    Mantas Šimkus

  2. Université d'Artois and CNRS, Lens, France

    Ivan Varzinczak

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Knorr, M. (2022). On Combining Ontologies and Rules. In: Šimkus, M., Varzinczak, I. (eds) Reasoning Web. Declarative Artificial Intelligence . Reasoning Web 2021. Lecture Notes in Computer Science(), vol 13100. Springer, Cham. https://doi.org/10.1007/978-3-030-95481-9_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-95481-9_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-95480-2

  • Online ISBN: 978-3-030-95481-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation