Extending Process Logs with Events from Supplementary Sources. Felix Mannhardt Massimiliano de Leoni, Hajo A.
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1 Extending Process Logs with Events from Supplementary Sources Felix Mannhardt Massimiliano de Leoni, Hajo A. Reijers
2 Heterogeneous Information Systems Systems Databases Join Event Logs? Department of Mathematics and Computer Science PAGE 1
3 Relating Events to Cases PK Event 1 Fine 1 2 Fine Join PK FK Event 22 1 Fine 23 2 Fine Event Amount ? Main Event Log Supplementary Events Department of Mathematics and Computer Science PAGE 2
4 Overview Main Event Log Process Model Alignment Extended Event Log Supplementary Events Department of Mathematics and Computer Science PAGE 3
5 Ingredients Main Event Log Supplementary Events A {A = 50} {E = 10} {P = 60}? Late Notice {Due = } {D = 60, X = 10} B {A = 110} {E = 10} {P = 60} {P = 110}? {D = 20, X = 10} {D = 30, X = 20} Process Model Amount Expenses A + E > P Fine Fine Credit A + E P Inv Debt EXtra Department of Mathematics and Computer Science PAGE 4 D = (A + E P) + X
6 Overview: Process Model Main Event Log Process Model Alignment Extended Event Log Supplementary Events Department of Mathematics and Computer Science PAGE 5
7 Process Model: Data Petri Nets A { A = 50 } { E = 10 } { P = 60 } Process Model Amount Expenses A + E > P Fine Fine Credit A + E P Inv Debt EXtra Department of Mathematics and Computer Science PAGE 6 D = (A + E P) + X
8 Data Petri Nets: Non-Conforming Trace B { A = 110 } { E = 10 } { P = 60 } { P = 110 } Amount Expenses Process Model A + E > P Fine Fine Credit A + E P Inv Debt EXtra Department of Mathematics and Computer Science PAGE 7 D = (A + E P) + X
9 Overview: Alignment Main Event Log Process Model Alignment Extended Event Log Supplementary Events Department of Mathematics and Computer Science PAGE 8
10 Alignment: Identify Missing Events Log { A = 110 } { E = 10 } { P = 60 } { P = 110 } >> Process { A = 110 } { E = 10 } { P = 60 } { P = 110 } {D = 10, X = 0} Missing Event Process Model Amount Expenses A + E > P Fine Fine Credit A + E P Inv Debt EXtra Department of Mathematics and Computer Science PAGE 9 D = (A + E P) + X
11 Alignment with Missing Events Alignment of Main Event Log A Log Process { A = 50 } { A = 50 } { E = 10 } { E = 10 } { P = 60 } { P = 60 } B Log Process { A = 110 } { A = 110 } { E = 10 } { E = 10 } { P = 60 } { P = 60 } { P = 110 } { P = 110 } >> {D = 10, X = 0} Department of Mathematics and Computer Science PAGE 10
12 Overview: Extending the Event Log Main Event Log Process Model Alignment Extended Event Log Supplementary Events Department of Mathematics and Computer Science PAGE 11
13 Extending the Event Log Alignment B {A = 110} {E = 10} {P = 60} {P = 110} {D = 10, X = 0} Supplementary Events Late Notice {Due = } Credit {D = 60, X = 10} Credit {D = 20, X = 10} Credit {D = 30, X = 20} Department of Mathematics and Computer Science PAGE 12
14 Events that relate to the Missing Activity Alignment B {A = 110} {E = 10} {P = 60} {P = 110} {D = 10, X = 0} Event Candidates Late Notice {Due = } Credit {D = 60, X = 10} Credit {D = 20, X = 10} Credit {D = 30, X = 20} Events relating the correct missing activity Department of Mathematics and Computer Science PAGE 13
15 Events with Compatible Timestamps B 3/6/2014 {A = 110} 15/7/2014 {E = 10} Alignment 1/8/2014 {P = 60} 1/9/2014 {P = 110} {D = 10, X = 0} Supplementary Events 10/7/2014 Credit {D = 60, X = 10} 10/10/ /10/2014 Credit {D = 20, X = 10} Credit {D = 30, X = 20} Events relating the correct missing activity Events with compatible timestamps Department of Mathematics and Computer Science PAGE 14
16 Events that Conform to Data Requirements B 3/6/2014 {A = 110} 15/7/2014 {E = 10} Alignment 1/8/2014 {P = 60} 1/9/2014 {P = 110} {D = 10, X = 0} Event Candidates D A + E P + X = 10 + X 10/10/ /10/2014 Credit {D = 20, X = 10} Credit {D = 30, X = 20} Events relating the correct missing activity Events with compatible timestamps Events conforming to data requirements Department of Mathematics and Computer Science PAGE 15
17 Choosing the correct Event B 3/6/2014 {A = 110} 15/7/2014 {E = 10} Alignment 1/8/2014 {P = 60} 1/9/2014 {P = 110} {D = 10, X = 0} Matching Events 10/10/ /10/2014 {D = 20, X = 10} {D = 30, X = 20} Random / Time-based etc.. B e 3/6/2014 {A = 110} 15/7/2014 {E = 10} Extended Trace 1/8/2014 {P = 60} 1/9/2014 {P = 110} 15/10/2014 {D = 30, X = 20} Department of Mathematics and Computer Science PAGE 16
18 Overview Main Event Log Process Model Alignment Extended Event Log Supplementary Events Department of Mathematics and Computer Science PAGE 17
19 Evaluation Real-life dataset of a Road Traffic Fines process ~ traces with ~ events Department of Mathematics and Computer Science PAGE 18
20 Evaluation Real-life dataset of a Road Traffic Fines process ~ traces with ~ events Two scenarios: For each, assume that an activity is done with a different system: Fine for Credit Split the Log into a Main Event Log and Supplementary Events Apply our approach Check how events are correlated Department of Mathematics and Computer Science PAGE 19
21 Measures % Perfectly correlated Same as original trace 10/10/2014 {D = 20, X = 10} 10/10/2014 {D = 20, X = 10} % Approx. correlated Mismatch in data or time 10/10/2014 {D = 20, X = 10} 12/10/2014 {D = 25, X = 5} % Wrongly correlated Missing / added events N/A 12/10/2014 {D = 25, X = 5} % Ignored Unmapped events 10/10/2014 {D = 20, X = 10} N/A Department of Mathematics and Computer Science PAGE 20
22 Evaluation Parameter to steer the reliability % Approx.: up to 80% % Ignored too high Department of Mathematics and Computer Science PAGE 21
23 Future Work Improve the evaluation Multiple events missing per trace Measures to compare wrt. wxisting work Find strategies for leftover non-mapped events How to use (estimated) activity durations: Better time constraints Improve the prototype: LogEnhancement package in ProM Department of Mathematics and Computer Science PAGE 22
24 Extending Process Logs with Events from Supplementary Sources Main Event Log Process Model Alignment Extended Event Log Supplementary Events Technique to extend an Event Log with Events Using an Alignment (with Data) to identify Gaps Finding the most likely Event to fill these Gaps Department of Mathematics and Computer Science PAGE 23
25 Remarks? Questions? Image source: Department of Mathematics and Computer Science
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