Selected Applications of Rules

Chapter
Part of the Intelligent Systems Reference Library book series (ISRL, volume 130)

Abstract

In this chapter we discuss several applications of rules and rule-based systems. Applications discussed in this chapter are mostly related to the areas of business and software engineering. They relevant for the applications of the semantic knowledge engineering approach. We begin with the discussion of the business rules approach. With time rules systems had to be integrated into other business management systems using business processes. Recently Web-based applications of the Semantic Web project played an important role. A number of past knowledge engineering experiences were placed in a new technological context. However, integration of classic rule-based systems with the Semantic Web technologies is quite challenging. Furthermore, we discuss some common uses of rules in the area of software engineering. A recent emerging computing paradigm of context-aware systems is also an important area for rules. Finally, we take a look at rules as a general programming paradigm.

References

  1. 1.
    Giurca, A., Gašević, D., Taveter, K. (eds.): Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches. Information Science Reference. Hershey, New York (May (2009)Google Scholar
  2. 2.
    Ambler, S.W.: Business Rules (2003). http://www.agilemodeling.com/artifacts/ businessRule.htm
  3. 3.
    von Halle, B.: Business Rules Applied: Building Better Systems Using the Business Rules Approach. Wiley, New York (2001)Google Scholar
  4. 4.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American (2001)Google Scholar
  5. 5.
    Hitzler, P., Krötzsch, M., Rudolph, S.: Foundations of Semantic Web Technologies. Chapman & Hall/CRC, Bocca Raton (2009)Google Scholar
  6. 6.
    Hay, D., Kolber, A., Healy, K.A.: Defining Business Rules - what they really are. Final Report. Technical report, Business Rules Group (2000)Google Scholar
  7. 7.
    Burns, A., Dobbing, B., Vardanega, T.: Defining business rules. what are they really? Technical Report revision 1.3, The Business Rules Group (2000)Google Scholar
  8. 8.
    Nalepa, G.J.: Business rules design and analysis approaches. In: Presentation given at the 6th European Business Rules Conference (2007)Google Scholar
  9. 9.
    Ross, R.G.: Principles of the Business Rule Approach, 1st edn. Addison-Wesley Professional, Boston (2003)Google Scholar
  10. 10.
    Object Management Group (OMG): Semantics of Business Vocabulary and Business Rules (SBVR) — Version 1.0, Framingham, Massachusetts (2008)Google Scholar
  11. 11.
    Object Management Group (OMG): Business Semantics of Business Rules – Request for Proposal (2004)Google Scholar
  12. 12.
    Nelson, M.L., Rariden, R.L., Sen, R.: A Lifecycle Approach towards Business Rules Management. In: Proceedings of the 41st Annual Hawaii International Conference on System Sciences, pp. 113–113 (2008)Google Scholar
  13. 13.
    Browne, P.: JBoss Drools Business Rules. Packt Publishing, Birmingham (2009)Google Scholar
  14. 14.
    Luckham, D.: Complex event processing (CEP). Softw. Eng. Notes 25(1), 99–100 (2000)CrossRefGoogle Scholar
  15. 15.
    van der Aalst, W.M.P., ter Hofstede, A.H.M., Weske, M.: Business process management: A survey. In: Proceedings of Business Process Management: International Conference, BPM. Lecture Notes in Computer Science, vol. 2678, pp. 1–12. Springer, Eindhoven, The Netherlands, 26–27 June 2003 (2003)Google Scholar
  16. 16.
    Knolmayer, G., Endl, R., Pfahrer, M.: Modeling processes and workflows by business rules. Business Process Management. Models, Techniques, and Empirical Studies, pp. 16–29. Springer, London, UK (2000)Google Scholar
  17. 17.
    Lee, R., Dale, B.: Business process management: a review and evaluation. Bus. Process Manag. J. 4(3), 214–225 (1998)CrossRefGoogle Scholar
  18. 18.
    OMG: Business Process Model and Notation (BPMN): Version 2.0 specification. Technical Report formal/2011-01-03, Object Management Group (2011)Google Scholar
  19. 19.
    Object Management Group (OMG): Decision model and notation request for proposal. Technical Report bmi/2011-03-04, Object Management Group, 140 Kendrick Street, Building A Suite 300, Needham, MA 02494, USA (2011)Google Scholar
  20. 20.
    Dumas, M., La Rosa, M., Mendling, J., Reijers, H.A.: Fundamentals of Business Process Management. Springer, Berlin (2013)CrossRefGoogle Scholar
  21. 21.
    Weske, M.: Business Process Management: Concepts, Languages, Architectures, 2nd edn. Springer, Berlin (2012)CrossRefGoogle Scholar
  22. 22.
    Davenport, T.H.: Process Innovation: Reengineering Work Through Information Technology. Harvard Business School Press, Boston (1993)Google Scholar
  23. 23.
    Hammer, M., Champy, J.: Reengineering the Corporation: A Manifesto for Business Revolution. Harper Business, New York (1993)Google Scholar
  24. 24.
    White, S.A., Miers, D.: BPMN Modeling and Reference Guide: Understanding and Using BPMN. Future Strategies Inc., Lighthouse Point, Florida, USA (2008)Google Scholar
  25. 25.
    Lindsay, A., Dawns, D., Lunn, K.: Business processes – attempts to find a definition. Inf. Softw. Technol. 45(15), 1015–1019 (2003). ElsevieGoogle Scholar
  26. 26.
    Owen, M., Raj, J.: BPMN and Business Process Management. Introduction to the new business process modeling standard. Technical report, OMG (2006)Google Scholar
  27. 27.
    WfMC: Workfow Management Coalition. http://www.wfmc.org/
  28. 28.
    Lawrence, P. (ed.): Workflow Handbook. Wiley, New York (1997)Google Scholar
  29. 29.
    zur Muehlen, M., Ho, D.T.Y.: Risk management in the BPM lifecycle. In: Business Process Management Workshops, pp. 454–466 (2005)Google Scholar
  30. 30.
    OMG: BPMN 2.0 by Example. Technical Report dtc/2010-06-02, Object Management Group (2010)Google Scholar
  31. 31.
    White, S.: Introduction to BPMN (2004). http://www.bpmn.org/Documents/Introduction20to20BPMN.pdf
  32. 32.
    Allweyer, T.: BPMN 2.0. Introduction to the Standard for Business Process Modeling. BoD, Norderstedt (2010)Google Scholar
  33. 33.
    Silver, B.: BPMN Method and Style. Cody-Cassidy Press (2009)Google Scholar
  34. 34.
    Chinosi, M., Trombetta, A.: BPMN: an introduction to the standard. Comput. Stand. Interfaces 34(1), 124–134 (2012)CrossRefGoogle Scholar
  35. 35.
    Wong, P.Y.H., Gibbons, J.: Formalisations and applications of bpmn. Sci. Comput. Program. 76(8), 633–650 (2011)CrossRefMATHGoogle Scholar
  36. 36.
    Krużel, T., Werewka, J.: Application of BPMN for the PMBOK standard modelling to scale project management efforts in IT enterprises. In: et al., Z.W., ed.: Information systems architecture and technology: information as the intangible assets and company value source, pp. 171–182. Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław (2011)Google Scholar
  37. 37.
    Ligęza, A.: A note on a logical model of an inference process : from ARD and RBS to BPMN. In: Małgorzata Nycz, M.L.O. (ed.) Knowledge acquisition and management. Research Papers of Wrocław University of Economics. 232 edn, pp. 41–49. Wrocław: Publishing House of Wrocław University of Economics (2011). ISSN 1899-3192Google Scholar
  38. 38.
    Lubke, D., Schneider, K., Weidlich, M.: Visualizing use case sets as bpmn processes. In: Requirements Engineering Visualization, 2008. REV ’08, pp. 21–25 (2008)Google Scholar
  39. 39.
    Szpyrka, M., Nalepa, G.J., Ligęza, A., Kluza, K.: Proposal of formal verification of selected BPMN models with Alvis modeling language. In: Brazier, F.M., Nieuwenhuis, K., Pavlin, G., Warnier, M., Badica, C. (eds.) Intelligent Distributed Computing V. Proceedings of the 5th International Symposium on Intelligent Distributed Computing – IDC 2011. Studies in Computational Intelligence, vol. 382, pp. 249–255. Springer, Delft, The Netherlands (2011)Google Scholar
  40. 40.
    Kluza, K., Maślanka, T., Nalepa, G.J., Ligęza, A.: Proposal of representing BPMN diagrams with XTT2-based business rules. In: Brazier, F.M.T., Nieuwenhuis, K., Pavlin, G., Warnier, M., Badica, C. (eds.) Intelligent Distributed Computing V. Proceedings of the 5th International Symposium on Intelligent Distributed Computing – IDC 2011. Studies in Computational Intelligence, vol. 382, pp. 243–248. Springer, Delft, The Netherlands (2011)Google Scholar
  41. 41.
    Kluza, K., Nalepa, G.J., Łysik, Ł.: Visual inference specification methods for modularized rulebases. Overview and integration proposal. In: Nalepa, G.J., Baumeister, J. (eds.) Proceedings of the 6th Workshop on Knowledge Engineering and Software Engineering (KESE6) at the 33rd German Conference on Artificial Intelligence September 21, 2010, Karlsruhe, Germany, Karlsruhe, Germany, pp. 6–17 (2010)Google Scholar
  42. 42.
    Nalepa, G.J., Kluza, K., Ernst, S.: Modeling and analysis of business processes with business rules. In: Beckmann, J. (ed.) Business Process Modeling: Software Engineering, Analysis and Applications. Business Issues, Competition and Entrepreneurship, pp. 135–156. Nova Science Publishers (2011)Google Scholar
  43. 43.
    Hohwiller, J., Schlegel, D., Grieser, G., Hoekstra, Y.: Integration of bpm and brm. In: Dijkman, R., Hofstetter, J., Koehler, J. (eds.) Business Process Model and Notation. Lecture Notes in Business Information Processing, vol. 95, pp. 136–141. Springer, Berlin (2011)CrossRefGoogle Scholar
  44. 44.
    Kluza, K.: Modeling of business processes consistent with business rules. PAR Pomiary Automatyka Robotyka 15(12), 194–195 (2011). ISSN 1427-9126Google Scholar
  45. 45.
    Di Bona, D., Lo Re, G., Aiello, G., Tamburo, A., Alessi, M.: A methodology for graphical modeling of business rules. In: 2011 5th UKSim European Symposium on Computer Modeling and Simulation (EMS), pp. 102–106 (2011)Google Scholar
  46. 46.
    Milanovic, M., Gaševic, D.: Towards a language for rule-enhanced business process modeling. In: Proceedings of the 13th IEEE international conference on Enterprise Distributed Object Computing, EDOC’09, pp. 59–68. IEEE Press, Piscataway, NJ, USA (2009)Google Scholar
  47. 47.
    Adams, M., ter Hofstede, A.H.M., Edmond, D., van der Aalst, W.M.P.: Worklets: A service-oriented implementation of dynamic flexibility in workflows. OTM Conferences 1, 291–308 (2006)Google Scholar
  48. 48.
    van Eijndhoven, T., Iacob, M.E., Ponisio, M.: Achieving business process flexibility with business rules. In: Proceedings of the 12th International IEEE Enterprise Distributed Object Computing Conference, 2008 EDOC ’08, pp. 95–104 (2008)Google Scholar
  49. 49.
    Müller, R., Greiner, U., Rahm, E.: Agent work: a workflow system supporting rule-based workflow adaptation. Data Knowl. Eng. 51(2), 223–256 (2004)CrossRefGoogle Scholar
  50. 50.
    zur Muehlen, M., Indulska, M., Kamp, G.: Business process and business rule modeling languages for compliance management: a representational analysis. In: Tutorials, posters, panels and industrial contributions at the 26th international conference on Conceptual modeling, vol. 83. ER ’07, pp. 127–132. Darlinghurst, Australia, Australia, Australian Computer Society, Inc (2007)Google Scholar
  51. 51.
    zur Muehlen, M., Indulska, M., Kittel, K.: Towards integrated modeling of business processes and business rules. In: 19th Australasian Conference on Information Systems ACIS 2008. Christchurch, New Zealand (2008)Google Scholar
  52. 52.
    Ouyang, C., Dumas, M., ter Hofstede, A.H., van der Aalst, W.M.: From bpmn process models to bpel web services. In: IEEE International Conference on Web Services (ICWS’06) (2006)Google Scholar
  53. 53.
    Ouyang, C., Wil M.P. van der Aalst, M.D., ter Hofstede, A.H.: Translating BPMN to BPEL. Technical report, Faculty of Information Technology, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia Department of Technology Management, Eindhoven University of Technology, GPO Box 513, NL-5600 MB, The Netherlands (2006)Google Scholar
  54. 54.
    Dijkman, R.M., Dumas, M., Ouyang, C.: Formal semantics and automated analysis of BPMN process models. preprint 7115. Technical report, Queensland University of Technology, Brisbane, Australia (2007)Google Scholar
  55. 55.
    Dijkman, R.M., Gorp, P.V.: Bpmn 2.0 execution semantics formalized as graph rewrite rules. In: Mendling, J., Weidlich, M., Weske, M. (eds.) Proceedings from the Business Process Modeling Notation – Second International Workshop, BPMN 2010. Lecture Notes in Business Information Processing, vol. 67, pp. 16–30. Springer, Potsdam, Germany 13–14 Oct 2010 (2011)Google Scholar
  56. 56.
    Speck, A., Feja, S., Witt, S., Pulvermüller, E., Schulz, M.: Formalizing business process specifications. Comput. Sci. Inf. Syst./ComSIS 8(2), 427–446 (2011)Google Scholar
  57. 57.
    Wong, P.Y.H., Gibbons, J.: A process semantics for bpmn. In: Liu, S., Maibaum, T.S.E., Araki, K. (eds.) ICFEM 2008 Proceedings from the 10th International Conference on Formal Engineering Methods. Lecture Notes in Computer Science, vol. 5256, pp. 355-374. Springer, Kitakyushu-City, Japan, 27–31 Oct 2008 (2008)Google Scholar
  58. 58.
    Lam, V.S.W.: Equivalences of BPMN processes. Serv. Oriented Comput. Appl. 3(3), 189–204 (2009)CrossRefGoogle Scholar
  59. 59.
    Lam, V.S.W.: Foundation for equivalences of BPMN models. Theor. Appl. Inf. 24(1), 33–66 (2012)Google Scholar
  60. 60.
    Ligęza, A.: BPMN - a logical model and property analysis. Decis. Making Manuf. Serv. 5(1–2), 57–67 (2011)MathSciNetMATHGoogle Scholar
  61. 61.
    Bray, T., Paoli, J., Sperberg-McQueen, C.M., Maler, E. (eds.): Extensible Markup Language (XML) 1.0, 2nd edn, Technical report, World Wide Web Consortium, W3C Recommendation (2000). http://www.w3.org/TR/REC-xml
  62. 62.
    Lassila, O., Swick, R.R.: Resource description framework (RDF) model and syntax specification. Technical report, World Wide Web Consortium, W3C Recommendation (1999). http://www.w3.org/TR/REC-rdf-syntax
  63. 63.
    Brickley, D., Guha, R.V.: RDF vocabulary description language 1.0: RDF schema. W3C recommendation, W3C (2004). http://www.w3.org/TR/2004/REC-rdf-schema-20040210/
  64. 64.
    Dean, M., Schreiber, G.: OWL Web Ontology Language reference. W3C recommendation, W3C (2004). http://www.w3.org/TR/2004/REC-owl-ref-20040210/
  65. 65.
    Seaborne, A., Prud’hommeaux, E.: SPARQL query language for RDF. W3C recommendation, W3C (2008). http://www.w3.org/TR/2008/REC-rdf-sparql-query-20080115/
  66. 66.
    Hitzler, P., Krötzsch, M., Parsia, B., Patel-Schneider, P.F., Rudolph, S.: OWL 2 Web Ontology Language – primer. W3C recommendation, W3C (2009)Google Scholar
  67. 67.
    Motik, B., Grau, B.C., Horrocks, I., Wu, Z., Fokoue, A., Lutz, C.: OWL 2 Web Ontology Language: Profiles. W3C recommendation, W3C (2009)Google Scholar
  68. 68.
    Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, Cambridge (2003)MATHGoogle Scholar
  69. 69.
    Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M.: SWRL: A semantic web rule language combining OWL and RuleML, W3C member submission 21 May 2004. Technical report, W3C (2004)Google Scholar
  70. 70.
    Grosof, B.N., Horrocks, I., Volz, R., Decker, S.: Description Logic Programs: combining logic programs with description logic. Proceedings of the Twelfth International World Wide Web Conference, WWW 2003, 48–57 (2003)CrossRefGoogle Scholar
  71. 71.
    Horrocks, I., Parsia, B., Patel-Schneider, P., Hendler, J.: Semantic web architecture: stack or two towers? In: Fages, F., Soliman, S. (eds.) Principles and Practice of Semantic Web Reasoning. Lecture Notes in Computer Science, vol. 3703, pp. 37–41. Springer (2005)Google Scholar
  72. 72.
    Eiter, T., Ianni, G., Polleres, A., Schindlauer, R., Tompits, H.: Reasoning with rules and ontologies. In: Proceedings of Summer School Reasoning Web 2006 REWERSE (2006). Lecture Notes in Computer Science, vol. 4126, pp. 93–127. Lisbon, Portugal (4–8 Sept 2006)Google Scholar
  73. 73.
    Bratko, I.: Prolog Programming for Artificial Intelligence, 3rd edn. Addison Wesley, Upper Saddle River (2000)MATHGoogle Scholar
  74. 74.
    Adrian, W.T., Nalepa, G.J., Kaczor, K., Noga, M.: Overview of selected approaches to rule representation on the Semantic Web. Technical Report CSLTR 2/2010, AGH University of Science and Technology (2010)Google Scholar
  75. 75.
    Antoniou, G., van Harmelen, F.: A Semantic Web Primer. The MIT Press, Cambridge (2008)Google Scholar
  76. 76.
    Nilsson, U., Małuszyński, J.: Logic, Programming and Prolog, 2nd edn. Wiley, New York (2000). http://www.ida.liu.se/~ulfni/lpp
  77. 77.
    Ullman, J.D.: Principles of Database and Knowledge-Base Systems, vol. I. Computer Science Press, New York (1988)Google Scholar
  78. 78.
    Kifer, M., Lausen, G., Wu, J.: Logical foundations of object-oriented and frame-based languages. J. ACM 42(4), 741–843 (1995)MathSciNetCrossRefMATHGoogle Scholar
  79. 79.
    Donini, F.M., Lenzerini, M., Nardi, D., Schaerf, A.: \(\cal{AL}\)-log: integrating datalog and description logics. J. Intell. Coop. Inf. Syst. 10, 227–252 (1998)CrossRefGoogle Scholar
  80. 80.
    Levy, A.Y., Rousset, M.C.: Combining horn rules and description logics in CARIN. Artif. Intell. 104(1–2), 165–209 (1998)MathSciNetCrossRefMATHGoogle Scholar
  81. 81.
    Motik, B., Horrocks, I., Rosati, R., Sattler, U.: Can OWL and logic programming live together happily ever after? Semant. Web - ISWC 2006, 501–514 (2006)Google Scholar
  82. 82.
    W3C Working Group: SWRL: A Semantic Web Rule Language Combining OWL and RuleML (2004). http://www.w3.org/Submission/SWRL
  83. 83.
    Parsia, B., Sirin, E., Grau, B.C., Ruckhaus, E., Hewlett, D.: Cautiously Approaching SWRL. Technical report, Technical report, University of Maryland (2005)Google Scholar
  84. 84.
    McGuinness, D.L., Welty, C., Smith, M.K.: OWL Web Ontology Language guide. W3C recommendation, W3C (2004). http://www.w3.org/TR/2004/REC-owl-guide-20040210
  85. 85.
    Boley, H., Tabet, S., Wagner, G.: Design rationale for RuleML: A markup language for semantic web rules. In: Cruz, I.F., Decker, S., Euzenat, J., McGuinness, D.L. (eds.) SWWS, pp. 381–401 (2001)Google Scholar
  86. 86.
    Motik, B., Sattler, U., Studer, R.: Query answering for OWL-DL with rules. In: Journal of Web Semantics, pp. 549–563. Springer (2004)Google Scholar
  87. 87.
    Krötzsch, M., Rudolph, S., Hitzler, P.: ELP: Tractable rules for OWL 2. In: 7th International Semantic Web Conference (ISWC2008) (2008)Google Scholar
  88. 88.
    Knorr, M., Hitzler, P., Maier, F.: Reconciling OWL and non-monotonic rules for the semantic web. In: Raedt, L.D., Bessière, C., Dubois, D., Doherty, P., Frasconi, P., Heintz, F., Lucas, P.J.F. (eds.) ECAI 2012 - 20th European Conference on Artificial Intelligence. Including Prestigious Applications of Artificial Intelligence (PAIS-2012) System Demonstrations Track. Frontiers in Artificial Intelligence and Applications, vol. 242, pp. 474–479. IOS Press, Montpellier, France, 27–31 Aug 2012 (2012)Google Scholar
  89. 89.
    Martínez, D.C., Hitzler, P.: Extending description logic rules. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, Ó., Presutti, V. (eds.) Proceedings of the Semantic Web: Research and Applications - 9th Extended Semantic Web Conference, ESWC 2012. Lecture Notes in Computer Science, vol. 7295, pp. 345–359. Springer, Heraklion, Crete, Greece, 27–31 May 2012 (2012)Google Scholar
  90. 90.
    Hitzler, P.: Recent advances concerning owl and rules. In: Invited Talk To 29th International Conference On Logic Programming (2013). http://www.iclp2013.org/files/downloads/iclp13_pascal.pdf
  91. 91.
    Mutharaju, R., Mateti, P., Hitzler, P.: Towards a rule based distributed OWL reasoning framework. In: Tamma, V.A.M., Dragoni, M., Gonçalves, R., Lawrynowicz, A. (eds.) Ontology Engineering - 12th International Experiences and Directions Workshop on OWL, OWLED 2015, co-located with ISWC 2015, Revised Selected Papers. Lecture Notes in Computer Science, vol. 9557, pp. 87–92. Springer, Bethlehem, PA, USA, 9–10 Oct. 2015 (2015)Google Scholar
  92. 92.
    Coutaz, J., Crowley, J.L., Dobson, S., Garlan, D.: Context is key. Commun. ACM 48(3), 49–53 (2005)CrossRefGoogle Scholar
  93. 93.
    Want, R., Falcao, V., Gibbons, J.: The active badge location system. ACM Trans. Inf. Syst. 10, 91–102 (1992)CrossRefGoogle Scholar
  94. 94.
    Schilit, B.N., Adams, N., Want, R.: Context-aware computing applications. In: Proceedings of the Workshop on Mobile Computing Systems and Applications. IEEE Computer Society, Washington, DC, USA, pp. 85–90 (1994)Google Scholar
  95. 95.
    Loke, S.W.: Representing and reasoning with situations for context-aware pervasive computing: a logic programming perspective. Knowl. Eng. Rev. 19(3), 213–233 (2004)CrossRefGoogle Scholar
  96. 96.
    Ranganathan, A., Campbell, R.H.: An infrastructure for context-awareness based on first order logic. Personal Ubiquitous Comput. 7(6), 353–364 (2003)CrossRefGoogle Scholar
  97. 97.
    Ranganathan, A., Al-Muhtadi, J., Campbell, R.H.: Reasoning about uncertain contexts in pervasive computing environments. IEEE Pervasive Comput. 3(2), 62–70 (2004)CrossRefGoogle Scholar
  98. 98.
    Hu, B., Wang, Z., Dong, Q.: A modeling and reasoning approach using description logic for context-aware pervasive computing. In: Lei, J., Wang, F., Deng, H., Miao, D. (eds.) Emerging Research in Artificial Intelligence and Computational Intelligence. Communications in Computer and Information Science, pp. 155–165. Springer, Berlin (2012)Google Scholar
  99. 99.
    Henricksen, K., Indulska, J.: Developing context-aware pervasive computing applications: models and approach. Pervasive Mob. Comput. 2(1), 37–64 (2006)CrossRefGoogle Scholar
  100. 100.
    Wang, X., Zhang, D., Gu, T., Pung, H.K.: Ontology based context modeling and reasoning using OWL. In: 2nd IEEE Conference on Pervasive Computing and Communications Workshops (PerCom 2004 Workshops), pp. 18–22. Orlando, FL, USA, 14–17 March 2004 (2004)Google Scholar
  101. 101.
    Chen, H., Perich, F., Finin, T.W., Joshi, A.: SOUPA: Standard ontology for ubiquitous and pervasive applications. In: 1st Annual International Conference on Mobile and Ubiquitous Systems (MobiQuitous 2004), Networking and Services, pp. 258–267. IEEE Computer Society, Cambridge, MA, USA, 22–25 Aug 2004 (2004)Google Scholar
  102. 102.
    Chen, H., Finin, T.W., Joshi, A.: Semantic web in the context broker architecture. In: PerCom, pp. 277–286. IEEE Computer Society (2004)Google Scholar
  103. 103.
    Ranganathan, A., McGrath, R.E., Campbell, R.H., Mickunas, M.D.: Use of ontologies in a pervasive computing environment. Knowl. Eng. Rev. 18(3), 209–220 (2003)CrossRefGoogle Scholar
  104. 104.
    Gu, T., Pung, H.K., Zhang, D.Q.: A middleware for building context-aware mobile services. In: 2004 IEEE 59th Vehicular Technology Conference, VTC 2004, vol. 5, pp. 2656–2660. Springer (2004)Google Scholar
  105. 105.
    Floch, J., Fra, C., Fricke, R., Geihs, K., Wagner, M., Lorenzo, J., Soladana, E., Mehlhase, S., Paspallis, N., Rahnama, H., Ruiz, P.A., Scholz, U.: Playing music – building context-aware and self-adaptive mobile applications. Softw.: Pract. Exp. 43(3), 359–388 (2013)Google Scholar
  106. 106.
    Jaroucheh, Z., Liu, X., Smith, S.: Recognize contextual situation in pervasive environments using process mining techniques. J. Ambient Intelligence and Humanized Comput. 2(1), 53–69 (2011)CrossRefGoogle Scholar
  107. 107.
    Brezillon, P., Pasquier, L., Pomerol, J.C.: Reasoning with contextual graphs. Eur. J. Operation. Res. 136(2), 290–298 (2002)CrossRefMATHGoogle Scholar
  108. 108.
    van der Aalst, W.M.P.: Process Mining - Discovery. Conformance and Enhancement of Business Processes. Springer, Berlin (2011)CrossRefMATHGoogle Scholar
  109. 109.
    Dey, A.K.: Understanding and using context. Pers. Ubiquitous Comput. 5(1), 4–7 (2001)CrossRefGoogle Scholar
  110. 110.
    Etter, R., Costa, P.D., Broens, T.: A rule-based approach towards context-aware user notification services. In: 2006 ACS/IEEE International Conference on Pervasive Services, pp. 281–284 (2006)Google Scholar
  111. 111.
    Wang, H., Mehta, R., Chung, L., Supakkul, S., Huang, L.: Rule-based context-aware adaptation: a goal-oriented approach. Int. J. Pervasive Comput. Commun. 8(3), 279–299 (2012)CrossRefGoogle Scholar
  112. 112.
    Dey, A.K.: Providing architectural support for building context-aware applications. Ph.D. thesis, Atlanta, GA, USA (2000) AAI9994400Google Scholar
  113. 113.
    Biegel, G., Cahill, V.: A framework for developing mobile, context-aware applications. In: 2004 Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications, PerCom 2004, pp. 361–365 (2004)Google Scholar
  114. 114.
    Dey, A.K.: Modeling and intelligibility in ambient environments. J. Ambient Intell. Smart Environ. 1(1), 57–62 (2009)MathSciNetGoogle Scholar
  115. 115.
    Ricci, F., Rokach, L., Shapira, B., Kantor, P.B.: Recommender Systems Handbook, 1st edn. Springer, New York (2010)MATHGoogle Scholar
  116. 116.
    Jannach, D., Zanker, M., Felfernig, A., Friedrich, G.: Recommender Systems An Introduction. Cambridge University Press, Cambridge (2011)Google Scholar
  117. 117.
    Adomavicius, G., Tuzhilin, A.: In: Context-Aware Recommender Systems, pp. 217–253. Springer, Boston(2011)Google Scholar
  118. 118.
    Bobek, S., Nalepa, G.J., Ślażyński, M.: Challenges for migration of rule-based reasoning engine to a mobile platform. In: Dziech, A., Czyżewski, A. (eds.) Multimedia Communications, Services and Security. Communications in Computer and Information Science, vol. 429, pp. 43–57. Springer, Berlin, Heidelberg (2014)CrossRefGoogle Scholar
  119. 119.
    Bobek, S., Nalepa, G.J.: Uncertain context data management in dynamic mobile environments. Future Gener. Comput. Syst. 66, 110–124 (2017)CrossRefGoogle Scholar
  120. 120.
    Sommerville, I.: Software Engineering, 7th edn. International Computer Science, Pearson Education Limited (2004)MATHGoogle Scholar
  121. 121.
    Guida, G., Lamperti, G., Zanella, M.: Software Prototyping in Data and Knowledge Engineering. Kluwer Academic Publishers, Norwell (1999)CrossRefMATHGoogle Scholar
  122. 122.
    Wagner, G.: How to design a general rule markup language. XML Technology for the Semantic Web (XSW 2002). Lecture Notes in Informatics, pp. 19–37. HU, Berlin (2002)Google Scholar
  123. 123.
    Ceri, S., Gottlob, G., Tanca, L.: Logic Programming and Databases. Springer, New York (1990)CrossRefGoogle Scholar
  124. 124.
    Seipel, D.: Practical applications of extended deductive databases in Datalog*. In: Proceedings of the 23rd Workshop on Logic Programming (WLP 2009) (2009)Google Scholar
  125. 125.
    OMG: Unified Modeling Language (OMG UML) version 2.2. superstructure. Technical Report formal/2009-02-02, Object Management Group (2009)Google Scholar
  126. 126.
    Pilone, D., Pitman, N.: UML 2.0 in a Nutshell. O’Reilly (2005)Google Scholar
  127. 127.
    Robin, J.: The object constraint language (OCL) (2007). http://www.cin.ufpe.br/~if710/2007/slides/OCL.ppt
  128. 128.
    Cuadra, D., Aljumaily, H., Castro, E., de Diego, M.V.: An OCL-based approach to derive constraint test cases for database applications. Int. J. Softw. Eng. Knowl. Eng. 21(5), 621–645 (2011)CrossRefGoogle Scholar
  129. 129.
    Lukichev, S., Wagner, G.: Visual rules modeling. In: Sixth International Andrei Ershov Memorial Conference Perspectives of System Informatics. Lecture Notes in Computer Science. Springer, Novosibirsk, Russia (2005)Google Scholar
  130. 130.
    Brockmans, S., Haase, P., Hitzler, P., Studer, R.: A metamodel and UML profile for rule-extended OWL DL ontologies. Lect. Notes Comput. Sci. 4011, 303–316 (2006)CrossRefGoogle Scholar
  131. 131.
    Stallman, R.M.: GNU Make Reference Manual. Samurai Media Limited (2015)Google Scholar
  132. 132.
    Nalepa, G.J., Kaczor, K.: Proposal of a rule-based testing framework for the automation of the unit testing process. In: Proceedings of the 17th IEEE International Conference on Emerging Technologies and Factory Automation ETFA 2012. Kraków, Poland, 28 Sept 2012 (2012)Google Scholar
  133. 133.
    W3C Working Group: Web services architecture w3c working group note 11 february 2004. Technical report, W3C (2004). https://www.w3.org/TR/ws-arch
  134. 134.
    Erl, T.: Service-Oriented Architecture (SOA): Concepts, Technology, and Design. Prentice Hall PTR, Upper Saddle River (2005)Google Scholar
  135. 135.
    Pant, K., Juric, M.: Business Process Driven SOA using BPMN and BPEL: From Business Process Modeling to Orchestration and Service Oriented Architecture. Packt Publishing, Birmingham (2008)Google Scholar
  136. 136.
    Rosenberg, F., Dustdar, S.: Business rules integration in bpel - a service-oriented approach. In: Seventh IEEE International Conference on E-Commerce Technology (CEC’05), pp. 476–479 (2005)Google Scholar
  137. 137.
    Ribarić, M. et al.: Modeling of Web Services using Reaction Rules. Information Science Reference. In: Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches. IGI Global (2009)Google Scholar
  138. 138.
    Semantic Annotations for WSDL Working Group: Semantic annotations for WSDL and XML schema. W3C recommendation 28 Aug 2007. Technical report, W3C (2007). http://www.w3.org/TR/sawsdl
  139. 139.
    Benslimane, D., Dustdar, S., Sheth, A.: Services mashups: the new generation of web applications. IEEE Internet Comput. 12(5), 13–15 (2008)CrossRefGoogle Scholar
  140. 140.
    Nalepa, G.J., Ligęza, A.: Designing reliable Web security systems using rule-based systems approach. In: Menasalvas, E., Segovia, J., Szczepaniak, P.S. (eds.) Advances in Web Intelligence. First International Atlantic Web Intelligence Conference AWIC 2003. Lecture Notes in Artificial Intelligence, vol. 2663, pp. 124–133. Springer, Berlin, Heidelberg, Madrid, Spain, 5-6 May 2003 (2003)Google Scholar
  141. 141.
    Nalepa, G.J., Ligęza, A.: Security systems design and analysis using an integrated rule-based systems approach. In: Szczepaniak, P.S., Kacprzyk, J., Niewiadomski, A. (eds.) Advances in Web Intelligence: 3rd international Atlantic Web Intelligence Conference AWIC 2005. Lecture Notes in Artificial Intelligence, vol. 3528, pp. 334–340. Springer, Berlin, Heidelberg, New York, Lodz, Poland, 6-9 June 2005 (2005)Google Scholar
  142. 142.
    Nalepa, G.J.: A unified firewall model for web security. In: Węgrzyn-Wolska, K.M., Szczepaniak, P.S. (eds.) Advances in Intelligent Web Mastering, Proceedings of the 5th Atlantic Web Intelligence Conference – AWIC’2007. Advances in Soft Computing, vol. 43, pp. 248–253. Springer, Berlin, Heidelberg, New York, Fontainebleau, France (2007)Google Scholar
  143. 143.
    Nalepa, G.J.: Application of the XTT rule-based model for formal design and verifcation of internet security systems. In Saglietti, F., Oster, N. (eds.) Computer safety, reliability, and security: 26th international conference, SAFECOMP 2007. Lecture Notes in Computer Science, vol. 4680, pp. 81–86. Springer, Berlin, Heidelberg, Nuremberg, Germany, 18–21 Sept 2007 (2007)Google Scholar
  144. 144.
    Paton, N.W., Díaz, O.: Active database systems. ACM Comput. Surv. 31(1), 63–103 (1999)CrossRefGoogle Scholar
  145. 145.
    Luckham, D.: The power of events: an introduction to complex event processing in distributed enterprise systems. Addison Wesley Professional, Boston (2002)Google Scholar
  146. 146.
    Paschke, A., Boley, H.: Rules Capturing Events and Reactivity. Information Science Reference. In: Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches. IGI Global (2009)Google Scholar
  147. 147.
    Paschke, A., Vincent, P., Alves, A., Moxey, C.: Tutorial on advanced design patterns in event processing. In: Bry, F., Paschke, A., Eugster, P.T., Fetzer, C., Behrend, A. (eds.) Proceedings of the Sixth ACM International Conference on Distributed Event-Based Systems, DEBS 2012, pp. 324–334. ACM, Berlin, Germany, 16–20 July 2012 (2012)Google Scholar
  148. 148.
    Paschke, A.: Reaction ruleml 1.0 for rules, events and actions in semantic complex event processing. In: Bikakis, A., Fodor, P., Roman, D. (eds.) Proceedings of Rules on the Web. From Theory to Applications - 8th International Symposium, RuleML 2014, Co-located with the 21st European Conference on Artificial Intelligence, ECAI 2014. Lecture Notes in Computer Science, vol. 8620, pp. 1–21. Springer, Prague, Czech Republic, 18–20 Aug 2014 (2014)Google Scholar
  149. 149.
    Paschke, A., Boley, H., Zhao, Z., Teymourian, K., Athan, T.: Reaction ruleml 1.0: Standardized semantic reaction rules. In: Bikakis, A., Giurca, A. (eds.) Proceedings of Rules on the Web: Research and Applications - 6th International Symposium, RuleML 2012. Lecture Notes in Computer Science, vol. 7438, pp. 100-119. Springer, Montpellier, France, 27–29 Aug 2012 (2012)Google Scholar
  150. 150.
    Covington, M.A., Nute, D., Vellino, A.: Prolog Programming in Depth. Prentice-Hall, Upper Saddle River (1996)MATHGoogle Scholar
  151. 151.
    Ostermayer, L., Seipel, D.: A prolog framework for integrating business rules into java applications. In: Nalepa, G.J., Baumeister, J. (eds.) Proceedings of 9th Workshop on Knowledge Engineering and Software Engineering (KESE9) co-located with the 36th German Conference on Artificial Intelligence (KI2013). CEUR Workshop Proceedings, vol. 1070, Koblenz, Germany, 17 Sept 2013 (2013). http://CEUR-WS.org
  152. 152.
    Aho, A.V., Kernighan, B.W., Weinberger, P.J.: The AWK Programming Language. Addison-Wesley, Boston (1988)MATHGoogle Scholar
  153. 153.
    Robbins, A.D.: GAWK: Effective AWK Programming. Free Software Foundation (2016)Google Scholar
  154. 154.
    Ostermayer, L.: Seamless Cooperation of Java and Prolog with CAPJA – A Connector Architecture for Prolog and Java. Ph.D. thesis, Univeristy of Würzburg (2017)Google Scholar
  155. 155.
    Clark, J.: XSL Transformations (XSLT) version 1.0 W3C recommendation 16 november 1999. Technical report, World Wide Web Consortium (W3C) (1999)Google Scholar
  156. 156.
    Frhwirth, T.: Constraint Handling Rules, 1st edn. Cambridge University Press, New York (2009)CrossRefGoogle Scholar
  157. 157.
    Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 3rd edn. Prentice-Hall, Upper Saddle River (2009)MATHGoogle Scholar
  158. 158.
    Hentenryck, P.V.: Constraint Satisfaction in Logic Programming. The MIT Press, Cambridge (1989)Google Scholar
  159. 159.
    Dechter, R.: Constraint Processing. Morgan Kaufmann, The Morgan Kaufmann Series in Artificial Intelligence (2003)MATHGoogle Scholar
  160. 160.
    Apt, K.R.: Principles of Constraint Programming. Cambridge University Press, Cambridge (2003)CrossRefMATHGoogle Scholar
  161. 161.
    Wagner, G., Damásio, C.V., Antoniou, G.: Towards a general web rule language. Int. J. Web Eng. Technol. 2(2/3), 181–206 (2005)CrossRefGoogle Scholar
  162. 162.
    Fowler, M.: Domain-Specific Languages. Addison Wesley, Boston (2011)Google Scholar

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© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.AGH University of Science and TechnologyKrakówPoland

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