Skip to main content
SpringerLink
Log in

Database Inconsistency Measures and Their Applications

  • Conference paper
  • First Online:
Information and Software Technologies (ICIST 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 756))

Included in the following conference series:

Abstract

We investigate the measuring of inconsistency of formal sentences, a field with increasing popularity in the literature about computer science, mathematics and logic. In particular, we look at database inconsistency measures, as featured in various publications in the literature. We focus on similarities and differences between inconsistency measures for databases and for sets of logic sentences. Also some differences to quality measures are pointed out. Moreover, we pace some characteristic applications of database inconsistency measures, which are related to monitoring, maintaining and improving the quality of stored data across updates.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

References

  1. Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley, Reading (1995)

    MATH  Google Scholar 

  2. Bauer, H.: Maß- und Integrationstheorie, 2nd edn. De Greuter, Berlin (1992)

    MATH  Google Scholar 

  3. Bertossi, L., Hunter, A., Schaub, T. (eds.): Inconsistency Tolerance. LNCS, vol. 3300. Springer, Heidelberg (2005)

    MATH  Google Scholar 

  4. Besnard, P.: Revisiting postulates for inconsistency measures. In: Fermé, E., Leite, J. (eds.) JELIA 2014. LNCS (LNAI), vol. 8761, pp. 383–396. Springer, Cham (2014). doi:10.1007/978-3-319-11558-0_27

    Google Scholar 

  5. Besnard, P.: Forgetting-based inconsistency measure. In: Schockaert, S., Senellart, P. (eds.) SUM 2016. LNCS (LNAI), vol. 9858, pp. 331–337. Springer, Cham (2016). doi:10.1007/978-3-319-45856-4_23

    Chapter  Google Scholar 

  6. Brewka, G., Dix, J., Konolige, K.: Nonmonotonic Reasoning: An Overview. CSLI Lecture Notes, vol. 73. CSLI Publications, Stanford (1997)

    MATH  Google Scholar 

  7. Ceri, S., Gottlob, G., Tanaka, L.: Logic Programming and Databases. Surveys in Computer Science. Springer, Heidelberg (1990)

    Book  Google Scholar 

  8. Clark, K.: Negation as failure. In: Gallaire, H., Minker, J. (eds.) Logic and Data Bases, pp. 293–322. Plenum, New York (1978)

    Chapter  Google Scholar 

  9. Codd, E.: A relational model of data for large shared data banks. CACM 13(6), 377–387 (1970)

    Article  MATH  Google Scholar 

  10. da Costa, N.: On the theory of inconsistent formal systems. Notre Dame J. Form. Log. 15(4), 497–510 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  11. de Bona, G., Finger, M.: Notes on measuring inconsistency in probabilistic logic. University of Sao Paulo (2014)

    Google Scholar 

  12. Decker, H.: The range form of databases and queries or: how to avoid floundering. In: Retti, J., Leidlmair, K. (eds.) 5th ÖGAI, pp. 114–123. Springer, Heidelberg (1989)

    Google Scholar 

  13. Decker, H.: Historical and computational aspects of paraconsistency in view of the logic foundation of databases. In: Bertossi, L., Katona, G.O.H., Schewe, K.-D., Thalheim, B. (eds.) SiD 2001. LNCS, vol. 2582, pp. 63–81. Springer, Heidelberg (2003). doi:10.1007/3-540-36596-6_4

    Chapter  Google Scholar 

  14. Decker, H.: A case for paraconsistent logic as a foundation of future information systems. In: 17th CAiSE Workshops, vol. 2, pp. 451–461. FEUP Ediçoes (2005)

    Google Scholar 

  15. Decker, H.: Quantifying the quality of stored data by measuring their integrity. In: Proceedings of ICADIWT 2009, Workshop SMM, pp. 823–828. IEEE (2009)

    Google Scholar 

  16. Decker, H.: How to confine inconsistency or, wittgenstein only scratched the surface. In: 8th ECAP, pp. 70–75. Technical University of Munich (2010)

    Google Scholar 

  17. Decker, H.: Measure-based inconsistency-tolerant maintenance of database integrity. In: Schewe, K.-D., Thalheim, B. (eds.) SDKB 2011. LNCS, vol. 7693, pp. 149–173. Springer, Heidelberg (2013). doi:10.1007/978-3-642-36008-4_7

    Chapter  Google Scholar 

  18. Decker, H.: New measures for maintaining the quality of databases. In: Murgante, B., Gervasi, O., Misra, S., Nedjah, N., Rocha, A.M.A.C., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2012. LNCS, vol. 7336, pp. 170–185. Springer, Heidelberg (2012). doi:10.1007/978-3-642-31128-4_13

    Chapter  Google Scholar 

  19. Decker, H., Martinenghi, D.: Inconsistency-tolerant integrity checking. IEEE Trans. Knowl. Data Eng. 23(2), 218–234 (2011)

    Article  Google Scholar 

  20. Decker, H., Martinenghi, D.: Modeling, measuring and monitoring the quality of information. In: Heuser, C.A., Pernul, G. (eds.) ER 2009. LNCS, vol. 5833, pp. 212–221. Springer, Heidelberg (2009). doi:10.1007/978-3-642-04947-7_26

    Chapter  Google Scholar 

  21. Decker, H., Misra, S.: Measure-based repair checking by integrity checking. In: Gervasi, O., et al. (eds.) ICCSA 2016. LNCS, vol. 9790, pp. 530–543. Springer, Cham (2016). doi:10.1007/978-3-319-42092-9_40

    Chapter  Google Scholar 

  22. Dubois, D., Prade, H.: Possibilistic logic: a retrospective and prospective view. Fuzzy Sets Syst. 144(1), 3–23 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  23. Gallaire, H., Minker, J., Nicolas, J.-M.: Logic and databases: a deductive approach. ACM Comput. Surv. 16(2), 153–185 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  24. Alchourron, C., Gardenfors, A., Makinson, D.: On the logic of theory change: partialo meet contraction and revision functions. J. Symb. Log. 50(2), 510–521 (1985)

    Article  MATH  Google Scholar 

  25. Gaye, M., Sall, O., Bousso, M., Lo, M.: Measuring inconsistencies propagation from change operation based on ontology partitioning. In: 11th SITIS, pp. 178–184 (2015)

    Google Scholar 

  26. Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: 5th ICLP, pp. 1070–1080. MIT Press (1988)

    Google Scholar 

  27. Grant, J.: Classifications for inconsistent theories. Notre Dame J. Form. Log. 19(3), 435–444 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  28. Grant, J., Hunter, A.: Measuring inconsistency in knowledgebases. J. Intell. Inf. Syst. 27(2), 159–184 (2006)

    Article  Google Scholar 

  29. Hand, D.: Statistics and the theory of measurement. J. R. Statist. Soc. Ser. A 159(3), 445–492 (1996)

    Article  Google Scholar 

  30. Hunter, A.: Measuring inconsistency in knowledge via quasi-classical models. In: 18th AAAI, pp. 68–73 (2002)

    Google Scholar 

  31. Hunter, A.: Evaluating significance of inonsistencies. In: 18th IJCAI, pp. 468–478 (2003)

    Google Scholar 

  32. Hunter, A., Konieczny, S.: Approaches to measuring inconsistent information. In: Bertossi, L., Hunter, A., Schaub, T. (eds.) Inconsistency Tolerance. LNCS, vol. 3300, pp. 191–236. Springer, Heidelberg (2005). doi:10.1007/978-3-540-30597-2_7

    Chapter  Google Scholar 

  33. Hunter, A., Konieczny, S.: On the measure of conflicts: shapley inconsistency values. AI 174(14), 1007–1026 (2010)

    MathSciNet  MATH  Google Scholar 

  34. Knight, K.: Measuring inconsistency. J. Philos. Log. 31, 77–98 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  35. Konieczny, S., Lang, J., Marquis, P.: Quantifying information and contradiction in propositional logic. In: 18th IJCAI, pp. 106–111 (2003)

    Google Scholar 

  36. Kowalski, R.: Logic for Problem Solving. North-Holland, New York (1979)

    MATH  Google Scholar 

  37. Kuhns, J.: Answering Questions by Computer: A Logical Study. Rand Corporation, Santa Monica (1967)

    Google Scholar 

  38. Lozinskii, E.: Information and evidence in logic systems. JETAI 6(2), 163–193 (1994)

    MATH  Google Scholar 

  39. Lang, J., Marquis, P.: Reasoning under inconsistency: a forgetting-based approach. Artif. Intell. 174(12–13), 799–823 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  40. Ma, Y., Guilin Qi, G., Hitzler, P.: Computing inconsistency measure based on paraconsistent semantics. J. Log. Comput. 21(6), 1257–1281 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  41. Popper, K.: Objective Knowledge: an Evolutionary Approach, Revised edn. Oxford University Press, Oxford (1979)

    Google Scholar 

  42. Priest, G.: Paraconsistent logic. In: Gabbay, D., Guenthner, F. (eds.) Handbook of Philosophical Logic, vol. 6. Kluwer, Dordrecht (2002)

    Google Scholar 

  43. Przymusinski, T.: Perfect model semantics. In: 5th ICLP, pp. 1081–1096. MIT Press (1988)

    Google Scholar 

  44. Qi, G., Hitzler, P.: Inconsistency-tolerant Reasoning with Networked Ontologies. Deliverable D1.2.4 of NeOn project. University of Karlsruhe (2008)

    Google Scholar 

  45. Reiter, R.: On closed world data bases. In: Gallaire, H., Minker, J. (eds.) Logic and Databases, pp. 55–76. Plenum, New York (1978)

    Google Scholar 

  46. Shannon, C.: A mathematical theory of communication. Bell Syst. Tech. J. 27(3), 379–423 (1948)

    Article  MathSciNet  MATH  Google Scholar 

  47. Thimm, M.: On the compliance of rationality postulates for inconsistency measures: a more or less complete picture. KI 31(1), 31–39 (2017)

    Google Scholar 

  48. Thimm, M., Wallner, J.: Some complexity results on inconsistency measurement. In: 15th KR, pp. 114–123. AAAI (2016)

    Google Scholar 

  49. van Emden, M., Kowalski, R.: The semantics of predicate logic as a programming language. J. ACM 23(4), 733–742 (1976)

    Article  MathSciNet  MATH  Google Scholar 

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

    MathSciNet  MATH  Google Scholar 

  51. Wikipedia: akri. https://en.wikipedia.org/wiki/Principle_of_explosion

Download references

Author information

Authors and Affiliations

  1. PROS, DSIC, Universidad Politecnica de Valencia, Valencia, Spain

    Hendrik Decker

  2. Covenant University, Canaanland, Ota, Nigeria

    Sanjay Misra

Authors
  1. Hendrik Decker
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sanjay Misra
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hendrik Decker .

Editor information

Editors and Affiliations

  1. Kaunas University of Technology, Kaunas, Lithuania

    Robertas Damaševičius

  2. Kaunas University of Technology, Kaunas, Lithuania

    Vilma Mikašytė

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Decker, H., Misra, S. (2017). Database Inconsistency Measures and Their Applications. In: Damaševičius, R., Mikašytė, V. (eds) Information and Software Technologies. ICIST 2017. Communications in Computer and Information Science, vol 756. Springer, Cham. https://doi.org/10.1007/978-3-319-67642-5_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67642-5_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67641-8

  • Online ISBN: 978-3-319-67642-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation