Encyclopedia of Big Data Technologies

2019 Edition
| Editors: Sherif Sakr, Albert Y. Zomaya

Declarative Process Mining

  • Fabrizio Maria MaggiEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-77525-8_92



In this chapter, we introduce the techniques existing in the literature in the context of declarative process mining, i.e., process mining techniques based on declarative process modeling languages. A declarative process mining technique is any technique that, in addition to taking as input an event log, takes as input or as output a (business) process model represented in a declarative process modeling notation. Declarative process mining techniques include techniques for process discovery, conformance checking, and compliance monitoring.


Process discovery, conformance checking, and process model enhancement are the three basic forms of process mining (van der Aalst 2016). In particular, process discovery aims at producing a process model based on example executions in an event log and without using any a priori information. Conformance checking pertains to the analysis of the process...

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


  1. Alberti M, Chesani F, Gavanelli M, Lamma E, Mello P, Torroni P (2008) Verifiable agent interaction in abductive logic programming: the SCIFF framework. ACM Trans Comput Log 9(4):29:1–29:43MathSciNetzbMATHCrossRefGoogle Scholar
  2. Baresi L, Guinea S (2005) Dynamo: dynamic monitoring of WS-BPEL processes. In: CSOC, vol 3826, pp 478–483Google Scholar
  3. Basin DA, Klaedtke F, Müller S, Pfitzmann B (2008) Runtime monitoring of metric first-order temporal properties. In: FSTTCS, vol 2, pp 49–60MathSciNetzbMATHGoogle Scholar
  4. Basin DA, Harvan M, Klaedtke F, Zalinescu E (2011) MONPOLY: monitoring usage-control policies. In: RV, vol 7186, pp 360–364Google Scholar
  5. Bellodi E, Riguzzi F, Lamma E (2010a) Probabilistic declarative process mining. In: KSEM, pp 292–303Google Scholar
  6. Bellodi E, Riguzzi F, Lamma E (2010b) Probabilistic logic-based process mining. In: CILC, pp 292–303Google Scholar
  7. Bernardi ML, Cimitile M, Di Francescomarino C, Maggi FM (2014a) Using discriminative rule mining to discover declarative process models with non-atomic activities. In: RuleML, pp 281–295Google Scholar
  8. Bernardi ML, Cimitile M, Maggi FM (2014b) Discovering cross-organizational business rules from the cloud. In: CIDM, pp 389–396Google Scholar
  9. Bernardi ML, Cimitile M, Di Francescomarino C, Maggi FM (2016) Do activity lifecycles affect the validity of a business rule in a business process? Inf Syst 62:42–59CrossRefGoogle Scholar
  10. Borrego D, Barba I (2014) Conformance checking and diagnosis for declarative business process models in data-aware scenarios. Expert Syst Appl 41(11): 5340–5352CrossRefGoogle Scholar
  11. Bragaglia S, Chesani F, Mello P, Montali M, Sottara D (2011) Fuzzy conformance checking of observed behaviour with expectations. In: AI*IA 2011, vol 6934, pp 80–91CrossRefGoogle Scholar
  12. Bragaglia S, Chesani F, Mello P, Montali M, Torroni P (2012) Reactive event calculus for monitoring global computing applications. In: Artikis A, Craven R, Kesim Çiçekli NK, Sadighi B, Stathis K (eds) Logic programs, norms and action, vol 7360. Springer, Heidelberg, pp 123–146CrossRefGoogle Scholar
  13. Burattin A, Maggi FM, van der Aalst WMP, Sperduti A (2012) Techniques for a posteriori analysis of declarative processes. In: EDOC, pp 41–50Google Scholar
  14. Burattin A, Cimitile M, Maggi FM (2014) Lights, camera, action! Business process movies for online process discovery. In: BPM workshops, pp 408–419Google Scholar
  15. Burattin A, Cimitile M, Maggi FM, Sperduti A (2015) Online discovery of declarative process models from event streams. IEEE Trans Serv Comput 8(6):833–846CrossRefGoogle Scholar
  16. Burattin A, Maggi FM, Sperduti A (2016) Conformance checking based on multi-perspective declarative process models. Expert Syst Appl 65:194–211CrossRefGoogle Scholar
  17. Chesani F, Lamma E, Mello P, Montali M, Riguzzi F, Storari S (2009a) Exploiting inductive logic programming techniques for declarative process mining. ToPNoC 2:278–295Google Scholar
  18. Chesani F, Mello P, Montali M, Riguzzi F, Sebastianis M, Storari S (2009b) Checking compliance of execution traces to business rules. In: BPM workshops, pp 134–145Google Scholar
  19. De Giacomo G, Vardi MY (2013) Linear temporal logic and linear dynamic logic on finite traces. In: IJCAI, pp 854–860Google Scholar
  20. De Giacomo G, De Masellis R, Grasso M, Maggi FM, Montali M (2014) Monitoring business metaconstraints based on LTL and LDL for finite traces. In: BPM, pp 1–17Google Scholar
  21. De Giacomo G, Maggi FM, Marrella A, Sardiña S (2016) Computing trace alignment against declarative process models through planning. In: ICAPS, pp 367–375Google Scholar
  22. De Giacomo G, Maggi FM, Marrella A, Patrizi F (2017) On the disruptive effectiveness of automated planning for LTLf-based trace alignment. In: AAAI, pp 3555–3561Google Scholar
  23. De Masellis R, Maggi FM, Montali M (2014) Monitoring data-aware business constraints with finite state automata. In: ICSSP, pp 134–143Google Scholar
  24. Debois S, Hildebrandt TT, Laursen PH, Ulrik KR (2017) Declarative process mining for DCR graphs. In: SAC, pp 759–764Google Scholar
  25. Di Ciccio C, Mecella M (2012) Mining constraints for artful processes. In: BIS, pp 11–23Google Scholar
  26. Di Ciccio C, Mecella M (2013) A two-step fast algorithm for the automated discovery of declarative workflows. In: CIDM, pp 135–142Google Scholar
  27. Di Ciccio C, Mecella M (2015) On the discovery of declarative control flows for artful processes. ACM Trans Manag Inf Syst 5(4):24:1–24:37CrossRefGoogle Scholar
  28. Di Ciccio C, Maggi FM, Mendling J (2014) Discovering target-branched declare constraints. In: BPM, pp 34–50Google Scholar
  29. Di Ciccio C, Maggi FM, Montali M, Mendling J (2015) Ensuring model consistency in declarative process discovery. In: BPM, Springer, pp 144–159. https://doi.org/10.1007/978-3-319-23063-4_9Google Scholar
  30. Di Ciccio C, Maggi FM, Mendling J (2016) Efficient discovery of target-branched declare constraints. Inf Syst 56:258–283CrossRefGoogle Scholar
  31. Di Ciccio C, Maggi FM, Montali M, Mendling J (2017) Resolving inconsistencies and redundancies in declarative process models. Inf Syst 64:425–446CrossRefGoogle Scholar
  32. Di Ciccio C, Maggi FM, Montali M, Mendling J (2018) On the relevance of a business constraint to an event log. Inf SystCrossRefGoogle Scholar
  33. Dwyer M, Avrunin G, Corbett J (1999) Patterns in property specifications for finite-state verification. In: ICSE, pp 411–420Google Scholar
  34. de Leoni M, Maggi FM, van der Aalst WMP (2012a) Aligning event logs and declarative process models for conformance checking. In: BPM, pp 82–97Google Scholar
  35. de Leoni M, Maggi FM, van der Aalst WMP (2012b) Aligning event logs and declarative process models for conformance checking. In: BPM, pp 82–97Google Scholar
  36. de Leoni M, Maggi FM, van der Aalst WM (2014) An alignment-based framework to check the conformance of declarative process models and to preprocess event-log data. Inf Syst 47:258–277CrossRefGoogle Scholar
  37. Ferilli S (2014) Woman: logic-based workflow learning and management. IEEE Trans Syst Man Cybern Syst 44(6):744–756CrossRefGoogle Scholar
  38. Giblin C, Müller S, Pfitzmann B (2006) From regulatory policies to event monitoring rules: towards model-driven compliance automation. Technical report. Report RZ 3662Google Scholar
  39. Gomez-Lopez M, Gasca R, Rinderle-Ma S (2013) Explaining the incorrect temporal events during business process monitoring by means of compliance rules and model-based diagnosis. In: EDOC workshops, pp 163–172Google Scholar
  40. Grando MA, van der Aalst WMP, Mans RS (2012) Reusing a declarative specification to check the conformance of different CIGs. In: BPM workshops, pp 188–199Google Scholar
  41. Grando MA, Schonenberg MH, van der Aalst WMP (2013) Semantic-based conformance checking of computer interpretable medical guidelines. In: BIOSTEC, vol 273, pp 285–300Google Scholar
  42. Haisjackl C, Zugal S, Soffer P, Hadar I, Reichert M, Pinggera J, Weber B (2013) Making sense of declarative process models: common strategies and typical pitfalls. In: BPMDS, pp 2–17Google Scholar
  43. Hallé S, Villemaire R (2008) Runtime monitoring of message-based workflows with data. In: ECOC, pp 63–72Google Scholar
  44. Kala T, Maggi FM, Di Ciccio C, Di Francescomarino C (2016) Apriori and sequence analysis for discovering declarative process models. In: EDOC, pp 1–9Google Scholar
  45. Kowalski RA, Sergot MJ (1986) A logic-based calculus of events. N Gener Comput 4(1):67–95zbMATHCrossRefGoogle Scholar
  46. Lamma E, Mello P, Montali M, Riguzzi F, Storari S (2007a) Inducing declarative logic-based models from labeled traces. In: BPM, pp 344–359Google Scholar
  47. Lamma E, Mello P, Riguzzi F, Storari S (2007b) Applying inductive logic programming to process mining. In: ILP, pp 132–146zbMATHGoogle Scholar
  48. Ly LT (2013) SeaFlows – a compliance checking framework for supporting the process lifecycle. PhD thesis, University of UlmGoogle Scholar
  49. Ly LT, Rinderle-Ma S, Knuplesch D, Dadam P (2011) Monitoring business process compliance using compliance rule graphs. In: OTM conferences (1), pp 82–99Google Scholar
  50. Ly LT, Maggi FM, Montali M, Rinderle-Ma S, van der Aalst WMP (2013) A framework for the systematic comparison and evaluation of compliance monitoring approaches. In: EDOC, pp 7–16Google Scholar
  51. Ly LT, Maggi FM, Montali M, Rinderle-Ma S, van der Aalst WMP (2015) Compliance monitoring in business processes: functionalities, application, and tool-support. Inf Syst 54:209–234CrossRefGoogle Scholar
  52. Maggi FM (2013) Declarative process mining with the declare component of ProM. In: BPM (Demos), vol 1021Google Scholar
  53. Maggi FM (2014) Discovering metric temporal business constraints from event logs. In: BIR, pp 261–275Google Scholar
  54. Maggi FM, Westergaard M (2014) Using timed automata for a Priori warnings and planning for timed declarative process models. Int J Cooperative Inf Syst 23(1)CrossRefGoogle Scholar
  55. Maggi FM, Westergaard M (2017) Designing software for operational decision support through coloured Petri nets. Enterprise IS 11(5):576–596CrossRefGoogle Scholar
  56. Maggi FM, Montali M, Westergaard M, van der Aalst WMP (2011a) Monitoring business constraints with linear temporal logic: an approach based on colored automata. In: BPM 2011, vol 6896, pp 132–147Google Scholar
  57. Maggi FM, Mooij AJ, van der Aalst WMP (2011b) User-guided discovery of declarative process models. In: CIDM, pp 192–199Google Scholar
  58. Maggi FM, Westergaard M, Montali M, van der Aalst WMP (2011c) Runtime verification of LTL-based declarative process models. In: RV 2011, vol 7186, pp 131–146Google Scholar
  59. Maggi FM, Bose RPJC, van der Aalst WMP (2012a) Efficient discovery of understandable declarative process models from event logs. In: CAiSE, pp 270–285Google Scholar
  60. Maggi FM, Montali M, van der Aalst WMP (2012b) An operational decision support framework for monitoring business constraints. In: FASE, pp 146–162Google Scholar
  61. Maggi FM, Bose RPJC, van der Aalst WMP (2013a) A knowledge-based integrated approach for discovering and repairing Declare maps. In: CAiSE, pp 433–448Google Scholar
  62. Maggi FM, Burattin A, Cimitile M, Sperduti A (2013b) Online process discovery to detect concept drifts in LTL-based declarative process models. In: OTM, pp 94–111Google Scholar
  63. Maggi FM, Dumas M, García-Bañuelos L, Montali M (2013c) Discovering data-aware declarative process models from event logs. In: BPM, pp 81–96Google Scholar
  64. Maggi FM, Montali M, Di Ciccio C, Mendling J (2016) Semantical vacuity detection in declarative process mining. In: BPM, pp 158–175Google Scholar
  65. Maggi FM, Di Ciccio C, Di Francescomarino C, Kala T (2018) Parallel algorithms for the automated discovery of declarative process models. Inf Syst. https://doi.org/10.1016/j.is.2017.12.002CrossRefGoogle Scholar
  66. Montali M, Pesic M, van der Aalst WMP, Chesani F, Mello P, Storari S (2010) Declarative specification and verification of service choreographies. ACM Trans Web 4(1):1–62CrossRefGoogle Scholar
  67. Montali M, Chesani F, Mello P, Maggi FM (2013a) Towards data-aware constraints in Declare. In: SAC, pp 1391–1396Google Scholar
  68. Montali M, Maggi FM, Chesani F, Mello P, van der Aalst WMP (2013b) Monitoring business constraints with the event calculus. ACM Trans Intell Syst Technol 5(1):17:1–17:30CrossRefGoogle Scholar
  69. Namiri K, Stojanovic N (2007) Pattern-based design and validation of business process compliance. In: CoopIS, On the move to meaningful internet systems, Springer, pp 59–76Google Scholar
  70. Narendra N, Varshney V, Nagar S, Vasa M, Bhamidipaty A (2008) Optimal control point selection for continuous business process compliance monitoring. In: IEEE SOLI, vol 2, pp 2536–2541Google Scholar
  71. Pesic M, Schonenberg H, van der Aalst WMP (2007) DECLARE: full support for loosely-structured processes. In: EDOC, pp 287–300Google Scholar
  72. Pichler P, Weber B, Zugal S, Pinggera J, Mendling J, Reijers HA (2011) Imperative versus declarative process modeling languages: an empirical investigation. In: BPM workshops, pp 383–394Google Scholar
  73. Pnueli A (1977) The temporal logic of programs. In: Annual IEEE symposium on foundations of computer science, pp 46–57Google Scholar
  74. Reijers HA, Slaats T, Stahl C (2013) Declarative modeling-an academic dream or the future for BPM? In: BPM, pp 307–322Google Scholar
  75. Rovani M, Maggi FM, de Leoni M, van der Aalst WMP (2015) Declarative process mining in healthcare. Expert Syst Appl 42(23):9236–9251CrossRefGoogle Scholar
  76. Santos EAP, Francisco R, Vieira AD, FR Loures E, Busetti MA (2012) Modeling business rules for supervisory control of process-aware information systems. In: BPM workshops, vol 100, pp 447–458CrossRefGoogle Scholar
  77. Schönig S, Di Ciccio C, Maggi FM, Mendling J (2016a) Discovery of multi-perspective declarative process models. In: ICSOC, pp 87–103Google Scholar
  78. Schönig S, Rogge-Solti A, Cabanillas C, Jablonski S, Mendling J (2016b) Efficient and customisable declarative process mining with SQL. In: CAiSE, pp 290–305Google Scholar
  79. Sebahi S (2012) Business process compliance monitoring: a view-based approach. PhD thesis, LIRISGoogle Scholar
  80. Silva NC, de Oliveira CAL, Albino FALA, Lima RMF (2014) Declarative versus imperative business process languages – a controlled experiment. In: ICEIS, pp 394–401Google Scholar
  81. Thullner R, Rozsnyai S, Schiefer J, Obweger H, Suntinger M (2011) Proactive business process compliance monitoring with event-based systems. In: EDOC workshops, pp 429–437Google Scholar
  82. van der Aalst WMP (2016) Process mining: data science in action. Springer, Berlin/HeidelbergCrossRefGoogle Scholar
  83. van der Aalst WMP, de Beer HT, van Dongen BF (2005) Process mining and verification of properties: an approach based on temporal logic. In: CoopIS, pp 130–147Google Scholar
  84. van der Aalst WMP, Pesic M, Schonenberg H (2009) Declarative workflows: balancing between flexibility and support. Comput Sci Res Dev 23(2):99–113CrossRefGoogle Scholar
  85. vanden Broucke SKLM, Vanthienen J, Baesens B (2014) Declarative process discovery with evolutionary computing. In: CEC, pp 2412–2419Google Scholar
  86. Westergaard M, Maggi FM (2011a) Declare: a tool suite for declarative workflow modeling and enactment. In: BPM (Demos)Google Scholar
  87. Westergaard M, Maggi FM (2011b) Modeling and verification of a protocol for operational support using coloured Petri nets. In: PETRI NETS, pp 169–188zbMATHGoogle Scholar
  88. Westergaard M, Maggi FM (2012) Looking into the future: using timed automata to provide a priori advice about timed declarative process models. In: CoopIS, pp 250–267Google Scholar
  89. Zugal S, Pinggera J, Weber B (2011) The impact of testcases on the maintainability of declarative process models. In: BMMDS/EMMSAD, pp 163–177Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of TartuTartuEstonia