Description
Constraint databases (CDBs) have been used in geographical information systems as a mechanism to represent the complex objects and information that can participate in this type of application. CDBs are proposed to represent geographical data by means of formulas described by constraints (equations, inequations, or Boolean combinations of both), since classic data types lack the expressiveness required for the representation of the full domain of data. The appearance of the object-relational constraint databases (ORCDB) was an evolution of the definition and implementation of CDBs to optimize query evaluation. ORCDBs enable complex information represented by means of constraints to be stored and queried in object-relational databases. This evolution shields the user from unnecessary details on how the complex information is stored and how the queries are evaluated, thereby enlarging the capacity of expressiveness for any commercial database management system.
ORCDBs permit...
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References
Araya I, Trombettoni G, Neveu B (2010) Making adaptive an interval constraint propagation algorithm exploiting monotonicity. In: Proceedings of the 16th international conference on principles and practice of constraint programming (CP’10). Springer-Verlag, Berlin/Heidelberg, pp 61–68
Basu S (1996) Algorithms in semi-algebraic geometry. New York University, New York
Benhamou F, Granvilliers L (2006) Continuous and interval constraints. In: Rossi F, van Beek P, Walsh T (eds) Handbook of constraint programming. Elsevier, Amsterdam/Boston, pp 571–604
Brisaboa NR, Luaces MR, Navarro G, Seco D (2013) Space-efficient representations of rectangle datasets supporting orthogonal range querying. Inf Syst 38(5):635–655
Brodsky A, Segal VE, Chen J, Exarkhopoulo PA (1999) The CCUBE constraint object-oriented database system. In: Proceedings of ACM SIGMOD international conference on management of data, 1–3 June 1999, Philadelphia, pp 577–579
Buchberger B (1985) Gröbner bases: an algorithmic method in polynomial ideal theory. In: Bose NK (ed) Multidimensional systems theory. Reidel Publishing Company, Dodrecht/Boston/Lancaster, pp 184–232
Dechter R (2003) Constraint processing. Morgan Kaufmann, San Francisco. ISBN:1558608907
Goldin D, Kutlu A, Song M (2003) Extending the constraint database framework. In: PCK50. ACM Press, New York, pp 42–54
Gómez-López MT, Gasca RM (2014) Using constraint programming in selection operators for constraint databases. Expert Syst Appl 41(15):6773–6785
Gómez-López MT, Ceballos R, Gasca RM, Valle CD (2009) Developing a labelled object-relational constraint database architecture for the projection operator. Data Knowl Eng 68(1):146–172
Granvilliers L, Goualard F, Benhamou F (1999) Box consistency through weak box consistency. In: 11th IEEE international conference on tools with artificial intelligence (ICTAI’99), Chicago, 8–10 Nov 1999, pp 373–380
Grumbach S, Rigaux P, Segoufin L (1998) The DEDALE system for complex spatial queries. In: SIGMOD conference. ACM, New York, pp 213–224
Jaffar J, Maher MJ (1994) Constraint logic programming: a survey. J Logic Program 19/20:503–581
Kanellakis PC, Kuper GM, Revesz PZ (1990) Constraint query languages. In: Proceedings of the ninth ACM SIGACT-SIGMOD-SIGART symposium on principles of database systems (PODS’90), Nashville, pp 299–313
Lin PL, Tan WH (2003) An efficient method for the retrieval of objects by topological relations in spatial database systems. Inf Process Manage 39(4): 543–559
Marriott K, Stuckey PJ (1998) Programming with constraints. An introduction. Simplification, optimization and implication. MIT, Cambridge
Revesz PZ (2001) Evaluation of queries. Introduction to constraint databases. Springer, New York
Revesz PZ (1998) Safe query languages for constraint databases. ACM Trans Database Syst 23(1): 58–99
Revesz PZ (2000) The DISCO system. In: Constraint databases. Springer, Berlin/Heidelberg, pp 383– 389
Revesz PZ (2002) Introduction to constraint databases. Texts in computer science. Springer, New York
Revesz PZ (2010) Introduction to databases: from biological to spatio-temporal, 1st edn. Springer Publishing Company Incorporated, New York
Revesz PZ, Li Y (1997) MLPQ: a linear constraint database system with aggregate operators. In: Proceedings of the international database engineering and applications symposium (IDEAS 1997), Concordia University, Montreal, 25–27 Aug 1997, pp 132–137
Revesz PZ, Wu S (2006) Spatiotemporal reasoning about epidemiological data. Artif Intell Med 38(2): 157–170
Revesz PZ, Chen R, Kanjamala P, Li Y, Liu Y, Wang Y (2000) The mlpq/gis constraint database system. In: Proceedings of the 2000 ACM SIGMOD international conference on management of data, Dallas, 16–18 May 2000. ACM p 601
Rochart G, Lorca X, Jussien N (2008) Choco. a java constraint programming library. Reference manual http://www.emnfr/z-info/choco-solver/
Tøssebro E, Nygård M (2011) Representing topological relationships for spatiotemporal objects. GeoInformatica 15(4):633–661
Wolfram R (2003) Mathematica 5. Reference Manual April
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This work has been partially funded by the Ministry of Science and Technology of Spain (TIN2015-63502-C3-2-R) and the European Regional Development Fund (ERDF/FEDER).
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Gómez-López, M., Gasca, R. (2017). Object Relational Constraint Databases for GIS. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-17885-1_1598
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DOI: https://doi.org/10.1007/978-3-319-17885-1_1598
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