Skip to main content
Springer Nature Link
Log in

Aspects of Dealing with Imperfect Data in Temporal Databases

  • Chapter
  • First Online:
Flexible Approaches in Data, Information and Knowledge Management

Part of the book series: Studies in Computational Intelligence ((SCI,volume 497))

  • 984 Accesses

Abstract

In reality, some objects or concepts have properties with a time-variant or time-related nature. Modelling these kinds of objects or concepts in a (relational) database schema is possible, but time-variant and time-related attributes have an impact on the consistency of the entire database. Therefore, temporal database models have been proposed to deal with this. Time itself can be at the source of imprecision, vagueness and uncertainty, since existing time measuring devices are inherently imperfect. Accordingly, human beings manage time using temporal indications and temporal notions, which may contain imprecision, vagueness and uncertainty. However, the imperfection in human-used temporal indications is supported by human interpretation, whereas information systems need extraordinary support for this. Several proposals for dealing with such imperfections when modelling temporal aspects exist. Some of these proposals consider the basis of the system to be the conversion of the specificity of temporal notions between used temporal expressions. Other proposals consider the temporal indications in the used temporal expressions to be the source of imperfection. In this chapter, an overview is given, concerning the basic concepts and issues related to the modelling of time as such or in (relational) database models and the imperfections that may arise during or as a result of this modelling. Next to this, a novel and currently researched technique for handling some of these imperfections is presented.

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    The presented proposal only deals with closed ill-known time intervals. Dealing with halfopen or open ill-known intervals is part of the current research of the authors.

References

  1. Allen, J.F.: Maintaining knowledge about temporal intervals. Commun. ACM 26, 832–843 (1983)

    Article  MATH  Google Scholar 

  2. Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20, 87–96 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  3. Bassiri, A., Malek, M., Alesheikh, A., Amirian, P.: Temporal relationships between rough time intervals. In: Gervasi, O., Taniar, D., Murgante, B., Lagan, A., Mun, Y., Gavrilova, M. (eds.) Computational Science and Its Applications ICCSA 2009. Lecture Notes in Computer Science, vol. 5592, pp. 543–552. Springer, Berlin (2009). http://dx.doi.org. 10.1007/978-3-642-02454-2_39

  4. Benthem, J.F.K.A.V.: The logic of time: a model-theoretic investigation into the varieties of temporal ontology and temporal discourse. Reidel, Hingham (1982)

    Google Scholar 

  5. Billiet, C., Pons, J.E., Matthé, T., De Tré, G., Pons Capote, O.: Bipolar fuzzy querying of temporal databases. In: Lecture Notes in Artificial Intelligence, vol. 7022, pp. 60–71. Springer, Ghent (2011)

    Google Scholar 

  6. Böhlen, M., Busatto, R., Jensen, C.: Point-versus interval-based temporal data models. In: Proceedings of the 14th International Conference on Data Engineering, pp. 192–200 (1998)

    Google Scholar 

  7. Bolour, A., Anderson, T.L., Dekeyser, L.J., Wong, H.K.T.: The role of time in information processing: a survey. ACM SIGMOD Record 12, 27–50 (1982)

    Article  Google Scholar 

  8. Bordogna, G., et al.: Advanced database query systems. In: Flexible Querying of Imperfect Temporal Metadata in Spatial Data Infrastructures: Techniques, Applications and Technologies, p. 140. IGI Global (2011). 10.4018/978-1-60960-475-2.ch006

  9. Bordogna, G., Carrara, P., Pagani, M., Pepe, M., Rampini, A.: Managing imperfect temporal metadata in the catalog services of spatial data infrastructures compliant with inspire. In: Carvalho, J.P., Dubois, D., Kaymak, U., da Costa Sousa, J.M. (eds.) IFSA/EUSFLAT conference, pp. 915–920 (2009). http://dblp.uni-trier.de/db/conf/eusflat/eusflat2009.html#BordognaCPPR09

  10. Burney, A., Mahmood, N., Abbas, Z.: Advances in fuzzy rough set theory for temporal databases. In: Proceedings of the 11th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases, AIKED’12, pp. 237–242. World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA (2009). http://dl.acm.org/citation.cfm?id=2183067.2183107

  11. Burney, A., Mahmood, N., Ahsan, K.: Tempr-pdm: a conceptual temporal relational model for managing patient data. In: Proceedings of the 9th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases, AIKED’10, pp. 237–243. World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA (2010). http://dl.acm.org/citation.cfm?id=1808036.1808078

  12. Burney, A., Mahmood, N., Jilani, T., Saleem, H.: Conceptual fuzzy temporal relational model (ftrm) for patient data. WSEAS Trans. Info. Sci. Appl. 7(5), 725–734 (2010). http://dl.acm.org/citation.cfm?id=1852534.1852546

  13. Chountas, P., Petrounias, I.: Modelling and representation of uncertain temporal information. Requir. Eng. 5, 144–156 (2000)

    Article  MATH  Google Scholar 

  14. Clifford, J., Tansel, A.U.: On an algebra for historical relational databases: two views. SIGMOD Rec. 14, 247–265 (1985)

    Article  Google Scholar 

  15. Corp., O.: Oracle database 11g., Workspace manager overview

    Google Scholar 

  16. Van der Cruyssen, B., De Caluwe R. and De Tré, G.: A theoretical fuzzy time model based on granularities. EUFIT’97, pp. 1127–1131 (1997)

    Google Scholar 

  17. De Caluwe, R., Van der Cruyssen, B., De Tré, G., Devos, F., Maesfranckx, P.: Fuzzy Time Indications in Natural Languages Interfaces, pp. 163–185. Kluwer Academic Publishers, Norwell (1997)

    Google Scholar 

  18. De Caluwe, R., De Tré, G., Van Der Cruyssen, B., Devos, F., Maesfranckx, P.: Time management in fuzzy and uncertain object-oriented databases. In: Knowledge Management in Fuzzy Databases, vol. 39, pp. 67–88. Physica-Verlag, Heidelberg (2000)

    Google Scholar 

  19. De Tré, G., De Caluwe, R., Van der Cruyssen, B.: Dealing with time in fuzzy and uncertain object-oriented database models. EUFIT’97, pp. 1157–1161 (1997)

    Google Scholar 

  20. De Tré, G., Zadrozny, E.A.: Dealing with positive and negative query criteria in fuzzy database querying bipolar satisfaction degrees. In: Proceedings of 8th International Conference on FQAS, pp. 593–604. Springer, Berlin (2009)

    Google Scholar 

  21. Dekhtyar, A., Ross, R., Subrahmanian, V.S.: Probabilistic temporal databases, I: algebra. ACM Trans. Database Syst. 26, 41–95 (2001)

    Article  MATH  Google Scholar 

  22. Devos, F., Maesfranckx, P., De Tré, G.: Granularity in the interpretation of around in approximative lexical time indications. J. Quant. Linguist. 5, 167–173 (1998)

    Article  Google Scholar 

  23. Devos, F., Van Gyseghem, N., Vandenberghe, R., De Caluwe, R.: Modelling vague lexical time expressions by means of fuzzy set theory. J. Quant. Linguist. 1(3), 189–194 (1994)

    Article  Google Scholar 

  24. Dey, D., Sarkar, S.: A probabilistic relational model and algebra. ACM Trans. Database Syst. 21(3), 339–369 (1996)

    Article  Google Scholar 

  25. Dieker, S., Güting, R.H.: Plug and play with query algebras: Secondo-a generic dbms development environment. In: Proceedings of the 2000 International Symposium on Database Engineering & Applications, IDEAS ’00, pp. 380–392. IEEE Computer Society, Washington, DC, USA (2000)

    Google Scholar 

  26. Dubois, D., HadjAli, A., Prade, H.: Fuzziness and uncertainty in temporal reasoning. J. Univ. Comput. Sci. 9(9), 1168–1194 (2003)

    MathSciNet  Google Scholar 

  27. Dubois, D., Prade, H.: Incomplete conjunctive information. Comput. Math. Appl. 15, 797–810 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  28. Dubois, D., Prade H.: Possibility Theory. Plenum Press, New York (1988)

    Google Scholar 

  29. Dubois, D., Prade, H.: Possibility Theory: An Approach to Computerized Processing of Uncertainty. Plenum Press, New York (1988)

    Book  MATH  Google Scholar 

  30. Dubois, D., Prade, H.: Processing fuzzy temporal knowledge. IEEE Trans. Syst. Man Cybern. B Cybern. 19, 729–744 (1989)

    Article  MathSciNet  Google Scholar 

  31. Dubois, D., Prade, H.: Bipolarity in flexible querying. In: Proceedings of the 5th International Conference on Flexible Query Answering Systems, FQAS ’02, pp. 174–182. Springer, London (2002)

    Google Scholar 

  32. Dubois, D., Prade, H.: Interval-valued fuzzy sets, possibility theory and imprecise probability. In: Proceedings of International Conference in Fuzzy Logic and Technology, pp. 314–319 (2005)

    Google Scholar 

  33. Dubois, D., Prade, H.: Rough sets and current trends in computing. In: Lecture Notes in Computer Science. Bipolar Representations in Reasoning, Knowledge Extraction and Decision Processes, vol. 4259, pp. 15–26. Springer, Heidelberg (2006)

    Google Scholar 

  34. Dubois, D., Prade, H.: Handling bipolar queries in Fuzzy Information Processing. In: Handbook of Research on Fuzzy Information Processing in Databases, pp. 97–114. Information Science Reference, New York (2008)

    Google Scholar 

  35. Dutta, S.: An event based fuzzy temporal logic. In: Proceedings of the Eighteenth International Symposium on Multiple-Valued Logic, pp. 64–71 (1988)

    Google Scholar 

  36. Dyreson, C.: Grandi, F.e.a.: A consensus glossary of temporal database concepts. SIGMOD Rec. 23, 52–64 (1994)

    Article  Google Scholar 

  37. Dyreson, C., Snodgrass, R.: Temporal granularity and indeterminacy: two sides of the same coin. Technical report tr 94–06, Computer Science Department, University of Arizona, Tucson, USA (1994).

    Google Scholar 

  38. Dyreson, C.E., Snodgrass, R.T.: Supporting valid-time indeterminacy. ACM Trans. Database Syst. 23, 1–57 (1998)

    Article  Google Scholar 

  39. Etzion, O., Jajodia, S., Sripada, S.: Temporal Databases: Research and Practice. Lecture Notes in Computer Science. Springer, Berlin (1998)

    Book  Google Scholar 

  40. Gadia., S.K.: A seamless generic extension of sql for querying temporal data. TR 92-02, Iowa State Univerity, Department of Computer Science (1992)

    Google Scholar 

  41. Galindo, J.: Fuzzy Databases: Modeling, Design, and Implementation. IGI Publishing, Hershey (2006)

    Google Scholar 

  42. Galindo, J., Medina, J.M.: Ftsql2: Fuzzy time in relational databases. In: EUSFLAT Conference ’01, pp. 47–50 (2001)

    Google Scholar 

  43. Garrido, C., Marin, N., Pons, O.: Fuzzy intervals to represent fuzzy valid time in a temporal relational database. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 17, 173–192 (2009)

    Article  MATH  Google Scholar 

  44. Grattan-Guinness, I.: Fuzzy membership mapped onto intervals and many-valued quantities. Math. Logic Quart. 22(1), 149–160 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  45. Güting, R.H., Schneider, M.: Moving objects databases. http://dna.fernuni-hagen.de/Lehre-offen/Kurse/1675/KE1.pdf

  46. Haddawy, P.: Believing change and changing belief. IEEE Trans. Syst. Man Cybern. Spec. Issue on High. Ord. Uncertainty 26 (1996)

    Google Scholar 

  47. Jahn, K.U.: Intervall-wertige mengen. Mathematische Nachrichten 68(1), 115–132 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  48. Jensen, C., Dyreson, C., Böhlen, M., Clifford, J., Elmasri, R., Gadia, S., Grandi, F., et al.: The consensus glossary of temporal database concepts—february 1998 version. In: Lecture Notes in Computer Science, pp. 367–405 (1998)

    Google Scholar 

  49. Jensen, C.S., Mark, L., Roussopoulos, N.: Incremental implementation model for relational databases with transaction time. IEEE Trans. Knowl. Data Eng. 3, 461–473 (1991)

    Article  Google Scholar 

  50. Jensen, C.S., Snodgrass, R.T., Soo, M.D.: The tsql2 data model. In: The TSQL2 Temporal Query, Language, pp. 153–238 (1995)

    Google Scholar 

  51. Kabanza, F., m. Stevenne, J., Wolper, P.: Handling infinite temporal data. J. Comput. Syst. Sci. 392–403 (1990)

    Google Scholar 

  52. Klein, W.: Time in language. Routledge, London (1994)

    Google Scholar 

  53. Klopprogge, M.R., Lockemann, P.C.: Modelling information preserving databases: consequences of the concept of time. In: Proceedings of the 9th International Conference on Very Large Data Bases, pp. 399–416. Morgan Kaufmann Publishers Inc., San Francisco (1983)

    Google Scholar 

  54. Knight, B., Ma, J.: Time representation: a taxonomy of temporal models. Artif. Intell. Rev. 7, 401–419 (1993)

    Article  Google Scholar 

  55. Lacroix, M., Lavency, P.: Preferences; putting more knowledge into queries. In: Proceedings of the 13th International Conference on Very Large Data Bases, VLDB ’87, pp. 217–225. Morgan Kaufmann Publishers Inc., San Francisco (1987)

    Google Scholar 

  56. Lakshmanan, L.V.S., Leone, N., Ross, R., Subrahmanian, V.S.: Probview: a flexible probabilistic database system. ACM Trans. Database Syst. 22(3), 419–469 (1997)

    Article  Google Scholar 

  57. Lin, H., Jensen, C.S., Böhlen, M.H.: Efficient conversion between temporal granularities. TR 19, The University of Arizona (1997)

    Google Scholar 

  58. Lorentzos, N.A.: A formal extension of the relational model for the representation of generic intervals. Ph.D. thesis, Birkbeck College, University of London (1988)

    Google Scholar 

  59. Zadeh, L.: Fuzzy sets. Inf. Control 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  60. Melton, J., Simon, A.R.: Understanding the new SQL: a complete guide. Morgan Kaufmann Publishers Inc., San Francisco (1993)

    Google Scholar 

  61. Mitra, D., et al.: A possibilistic interval constraint problem: fuzzy temporal reasoning. In: Proceedings of the Third IEEE Conference on Fuzzy Systems: IEEE World Congress on Computational Intelligence, vol. 2, pp. 1434–1439 (1994)

    Google Scholar 

  62. Nagypál, G., Motik, B.: A fuzzy model for representing uncertain, subjective, and vague temporal knowledge in ontologies. In: On The Move to Meaningful Internet Systems 2003: CoopIS, DOA, and ODBASE, LNCS, vol. 2888, pp. 906–923. Springer, Heidelberg (2003)

    Google Scholar 

  63. Nascimento, M.A., Eich, M.H.: Decision time in temporal databases. In: Proceedings of the Second International Workshop on Temporal Representation and Reasoning, pp. 157–162 (1995)

    Google Scholar 

  64. Navathe, S., Ahmed, R.: Tsql: a language interface for history databases. In: Workshop on Temporal Databases-TDB, pp. 109–122 (1987)

    Google Scholar 

  65. Ohlbach, H.J.: Relations between fuzzy time intervals. In: International Symposium on Temporal Representation and Reasoning, pp. 44–51 (2004)

    Google Scholar 

  66. Pawlak, Z., Grymala-Busse, J., Slowinski, R., Ziarko, W.: Rough sets. Commun. ACM 38(6), 88–95 (1995)

    Google Scholar 

  67. Pons, J., Bronselaer, A., Pons, O., de Tre, G.: Possibilistic evaluation of fuzzy temporal intervals. In: Sainz, G., Alcalá, J. (eds.) Actas del XVI Congreso Espa nol sobre Tecnologías y Lógica Fuzzy. Valladolid, Spain (2012)

    Google Scholar 

  68. Bronselaer, A., Pons, J.E., De Tré, G., Pons, O.: Possibilistic evaluation of sets. Int, J. Unc. Fuzz. Knowl. Based Syst. 21(3), 325–346 (2013)

    Google Scholar 

  69. Postgree: Temporal postgreesql (2011). http://pgfoundry.org/projects/temporal/

  70. Qiang, Y., Asmussen, K., Delafontaine, M., De Tré, G., Stichelbaut, B., De Maeyer, P., Van de Weghe, N.: Visualising rough time intervals in a two-dimensional space. In: 2009 IFSA World Congress / EUSFLAT Conference, Proceedings (2001)

    Google Scholar 

  71. Sambuc, R.: Fonctions \(\phi \)-floues. application l’aide au diagnostic en pathologie thyroidienne. Ph.D. thesis, Univ. Marseille, France (1975)

    Google Scholar 

  72. Sarda, N.L.: Extensions to sql for historical databases. IEEE Trans. Knowl. Data Eng. 2, 220–230 (1990)

    Article  Google Scholar 

  73. Schockaert, S., De Cock, M., Kerre, E.: Fuzzifying allen’s temporal interval relations. IEEE Trans. Fuzzy Syst. 16(2), 517–533 (2008)

    Google Scholar 

  74. Shackle, G.: Decision, order and time in human affairs. Cambridge University Press, Cambridge (1961)

    Google Scholar 

  75. Snodgrass, R.: The temporal query language tquel. In: Proceedings of the 3rd ACM SIGACT-SIGMOD Symposium on Principles of Database Systems, PODS ’84, pp. 204–213. ACM, New York (1984)

    Google Scholar 

  76. Snodgrass, R.T., Jensen, C.S., Jensen, C.S., Jensen, C.S., Steiner, A., Böhlen, M.H., Busatto, R., Gregersen, H.: Transitioning temporal support in tsql2 to sql3. In: Etzion, O., Jajodia, S., Sripada S. (eds.) Temporal Databases: Research and Practice, Lecture Notes in Computer Science, vol. 1399. Springer, Berlin (1998)

    Google Scholar 

  77. Soysangwarn, S., Chittayasothorn, S.: Toward fuzzy temporal databases with temporal fuzzy linguistic terms. In: Second International Conference on the Applications of Digital Information and Web Technologies, 2009. ICADIWT ’09, pp. 8–13 (2009). 10.1109/ICADIWT.2009.5273853

  78. Teradata: Teradata Temporal (2011). http://www.teradata.com/database/teradata-temporal/

  79. TimeDB: A temporal relational dbms (2011) http://www.timeconsult.com/Software/Software.html

  80. Virant, J., Zimic, N.: Attention to time in fuzzy logic. Fuzzy Sets Syst. 82(1), 39–49 (1996)

    Article  MathSciNet  Google Scholar 

  81. Wang, X.S., Jajodia, S., Subrahmanian, V.S.: Temporal modules: an approach toward federated temporal databases. In: Information Systems, pp. 227–236 (1993)

    Google Scholar 

  82. Wu, Y., Jajodia, S., Wang, X.: Temporal database bibliography update. In: O. Etzion, S. Jajodia, S. Sripada (eds.) Temporal Databases: Research and Practice, Lecture Notes in Computer Science, vol. 1399, pp. 338–366. Springer, Berlin (1998)

    Google Scholar 

  83. Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning—I. Inf. Sci. 8(3), 199–249 (1975)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

Part of this research is supported by the grant BES-2009-013805 within the research project TIN2008-02066: Fuzzy Temporal Information treatment in relational DBMS.

Author information

Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, Escuela Técnica Superior de Ingeniería Informática, Universidad de Granada, C/Periodista Daniel Saucedo Aranda s/n, 18071, Granada, Spain

    José Pons & Olga Pons

  2. Department of Telecommunications and Information Processing, Ghent University, St.-Pietersnieuwstraat 41, 9000, Gent, Belgium

    Christophe Billiet & Guy De Tré

Authors
  1. José Pons
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christophe Billiet
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Olga Pons
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guy De Tré
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to José Pons .

Editor information

Editors and Affiliations

  1. IRISA/ENSSAT, Université de Rennes 1, Lannion Cedex, France

    Olivier Pivert

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Sławomir Zadrożny

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Pons, J., Billiet, C., Pons, O., De Tré, G. (2014). Aspects of Dealing with Imperfect Data in Temporal Databases. In: Pivert, O., Zadrożny, S. (eds) Flexible Approaches in Data, Information and Knowledge Management. Studies in Computational Intelligence, vol 497. Springer, Cham. https://doi.org/10.1007/978-3-319-00954-4_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00954-4_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-00953-7

  • Online ISBN: 978-3-319-00954-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics