The eventdataR package contains several real-life and artificial event logs. Each can be loaded using the data function. The currently available event logs are listed below. More event logs will be added in the future.

Artifical data

Patients

Artificial eventlog about patients arriving in an emergency department of a hospital. This event log was used as the running example in the journal paper entitled Retrieving batch organisation of work insights from event logs.

library(eventdataR)
patients %>% summary
## Number of events:  5442
## Number of cases:  500
## Number of traces:  7
## Number of distinct activities:  7
## Average trace length:  10.884
## 
## Start eventlog:  2017-01-02 11:41:53
## End eventlog:  2018-05-05 07:16:02
##                   handling      patient          employee 
##  Blood test           : 474   Length:5442        r1:1000  
##  Check-out            : 984   Class :character   r2:1000  
##  Discuss Results      : 990   Mode  :character   r3: 474  
##  MRI SCAN             : 472                      r4: 472  
##  Registration         :1000                      r5: 522  
##  Triage and Assessment:1000                      r6: 990  
##  X-Ray                : 522                      r7: 984  
##  handling_id        registration_type      time                    
##  Length:5442        complete:2721     Min.   :2017-01-02 11:41:53  
##  Class :character   start   :2721     1st Qu.:2017-05-06 17:15:18  
##  Mode  :character                     Median :2017-09-08 04:16:50  
##                                       Mean   :2017-09-02 20:52:34  
##                                       3rd Qu.:2017-12-22 15:44:11  
##                                       Max.   :2018-05-05 07:16:02  
##                                                                    
##      .order    
##  Min.   :   1  
##  1st Qu.:1361  
##  Median :2722  
##  Mean   :2722  
##  3rd Qu.:4082  
##  Max.   :5442  
## 

Real-life data

Sepsis

sepsis
## Event log consisting of:
## 15214 events
## 846 traces
## 1050 cases
## 16 activities
## 15214 activity instances
## 
## # A tibble: 15,214 x 34
##    case_id activity     lifecycle resource timestamp             age   crp
##    <chr>   <fct>        <fct>     <fct>    <dttm>              <int> <dbl>
##  1 A       ER Registra~ complete  A        2014-10-22 11:15:41    85   NA 
##  2 A       Leucocytes   complete  B        2014-10-22 11:27:00    NA   NA 
##  3 A       CRP          complete  B        2014-10-22 11:27:00    NA  210.
##  4 A       LacticAcid   complete  B        2014-10-22 11:27:00    NA   NA 
##  5 A       ER Triage    complete  C        2014-10-22 11:33:37    NA   NA 
##  6 A       ER Sepsis T~ complete  A        2014-10-22 11:34:00    NA   NA 
##  7 A       IV Liquid    complete  A        2014-10-22 14:03:47    NA   NA 
##  8 A       IV Antibiot~ complete  A        2014-10-22 14:03:47    NA   NA 
##  9 A       Admission NC complete  D        2014-10-22 14:13:19    NA   NA 
## 10 A       CRP          complete  B        2014-10-24 09:00:00    NA 1090.
## # ... with 15,204 more rows, and 27 more variables: diagnose <chr>,
## #   diagnosticartastrup <chr>, diagnosticblood <chr>, diagnosticecg <chr>,
## #   diagnosticic <chr>, diagnosticlacticacid <chr>,
## #   diagnosticliquor <chr>, diagnosticother <chr>, diagnosticsputum <chr>,
## #   diagnosticurinaryculture <chr>, diagnosticurinarysediment <chr>,
## #   diagnosticxthorax <chr>, disfuncorg <chr>, hypotensie <chr>,
## #   hypoxie <chr>, infectionsuspected <chr>, infusion <chr>,
## #   lacticacid <dbl>, leucocytes <chr>, oligurie <chr>,
## #   sirscritheartrate <chr>, sirscritleucos <chr>,
## #   sirscrittachypnea <chr>, sirscrittemperature <chr>,
## #   sirscriteria2ormore <chr>, activity_instance_id <chr>, .order <int>

Hospital Log

hospital
## Event log consisting of:
## 150291 events
## 981 traces
## 1143 cases
## 624 activities
## 150291 activity instances
## 
## # A tibble: 150,291 x 98
##    case_id  activity      lifecycle group     timestamp           CASE_age
##    <chr>    <fct>         <fct>     <fct>     <dttm>                 <int>
##  1 00000000 1e consult p~ complete  Radiothe~ 2005-01-03 00:00:00       33
##  2 00000000 administrati~ complete  Radiothe~ 2005-01-03 00:00:00       33
##  3 00000000 verlosk.-gyn~ complete  Nursing ~ 2005-01-05 00:00:00       33
##  4 00000000 echografie  ~ complete  Obstetri~ 2005-01-05 00:00:00       33
##  5 00000000 1e consult p~ complete  Nursing ~ 2005-01-05 00:00:00       33
##  6 00000000 administrati~ complete  Nursing ~ 2005-01-05 00:00:00       33
##  7 00000000 simulator - ~ complete  Radiothe~ 2005-01-24 00:00:00       33
##  8 00000000 behandeltijd~ complete  Radiothe~ 2005-01-31 00:00:00       33
##  9 00000000 teletherapie~ complete  Radiothe~ 2005-01-31 00:00:00       33
## 10 00000000 aanname labo~ complete  General ~ 2005-02-15 00:00:00       33
## # ... with 150,281 more rows, and 92 more variables: `CASE_age:1` <int>,
## #   `CASE_age:2` <int>, `CASE_age:3` <int>, `CASE_age:4` <int>,
## #   `CASE_age:5` <chr>, CASE_diagnosis <chr>,
## #   CASE_diagnosis_treatment_combination_id <int>,
## #   `CASE_diagnosis_treatment_combination_id:1` <int>,
## #   `CASE_diagnosis_treatment_combination_id:10` <chr>,
## #   `CASE_diagnosis_treatment_combination_id:11` <chr>,
## #   `CASE_diagnosis_treatment_combination_id:12` <chr>,
## #   `CASE_diagnosis_treatment_combination_id:13` <chr>,
## #   `CASE_diagnosis_treatment_combination_id:14` <chr>,
## #   `CASE_diagnosis_treatment_combination_id:15` <chr>,
## #   `CASE_diagnosis_treatment_combination_id:2` <int>,
## #   `CASE_diagnosis_treatment_combination_id:3` <int>,
## #   `CASE_diagnosis_treatment_combination_id:4` <int>,
## #   `CASE_diagnosis_treatment_combination_id:5` <int>,
## #   `CASE_diagnosis_treatment_combination_id:6` <chr>,
## #   `CASE_diagnosis_treatment_combination_id:7` <chr>,
## #   `CASE_diagnosis_treatment_combination_id:8` <chr>,
## #   `CASE_diagnosis_treatment_combination_id:9` <chr>,
## #   CASE_diagnosis_code <chr>, `CASE_diagnosis_code:1` <chr>,
## #   `CASE_diagnosis_code:10` <chr>, `CASE_diagnosis_code:11` <chr>,
## #   `CASE_diagnosis_code:12` <chr>, `CASE_diagnosis_code:13` <chr>,
## #   `CASE_diagnosis_code:14` <chr>, `CASE_diagnosis_code:15` <chr>,
## #   `CASE_diagnosis_code:2` <chr>, `CASE_diagnosis_code:3` <chr>,
## #   `CASE_diagnosis_code:4` <chr>, `CASE_diagnosis_code:5` <int>,
## #   `CASE_diagnosis_code:6` <chr>, `CASE_diagnosis_code:7` <chr>,
## #   `CASE_diagnosis_code:8` <chr>, `CASE_diagnosis_code:9` <chr>,
## #   `CASE_diagnosis:1` <chr>, `CASE_diagnosis:10` <chr>,
## #   `CASE_diagnosis:11` <chr>, `CASE_diagnosis:12` <chr>,
## #   `CASE_diagnosis:13` <chr>, `CASE_diagnosis:14` <chr>,
## #   `CASE_diagnosis:15` <chr>, `CASE_diagnosis:2` <chr>,
## #   `CASE_diagnosis:3` <chr>, `CASE_diagnosis:4` <chr>,
## #   `CASE_diagnosis:5` <chr>, `CASE_diagnosis:6` <chr>,
## #   `CASE_diagnosis:7` <chr>, `CASE_diagnosis:8` <chr>,
## #   `CASE_diagnosis:9` <chr>, CASE_specialism_code <int>,
## #   `CASE_specialism_code:1` <int>, `CASE_specialism_code:10` <chr>,
## #   `CASE_specialism_code:11` <chr>, `CASE_specialism_code:12` <chr>,
## #   `CASE_specialism_code:13` <chr>, `CASE_specialism_code:14` <chr>,
## #   `CASE_specialism_code:15` <chr>, `CASE_specialism_code:2` <int>,
## #   `CASE_specialism_code:3` <int>, `CASE_specialism_code:4` <int>,
## #   `CASE_specialism_code:5` <int>, `CASE_specialism_code:6` <chr>,
## #   `CASE_specialism_code:7` <chr>, `CASE_specialism_code:8` <chr>,
## #   `CASE_specialism_code:9` <chr>, CASE_treatment_code <int>,
## #   `CASE_treatment_code:1` <int>, `CASE_treatment_code:10` <chr>,
## #   `CASE_treatment_code:11` <chr>, `CASE_treatment_code:12` <chr>,
## #   `CASE_treatment_code:13` <chr>, `CASE_treatment_code:14` <chr>,
## #   `CASE_treatment_code:15` <chr>, `CASE_treatment_code:2` <int>,
## #   `CASE_treatment_code:3` <int>, `CASE_treatment_code:4` <int>,
## #   `CASE_treatment_code:5` <int>, `CASE_treatment_code:6` <chr>,
## #   `CASE_treatment_code:7` <chr>, `CASE_treatment_code:8` <chr>,
## #   `CASE_treatment_code:9` <chr>, activity_code <chr>,
## #   number_of_executions <int>, producer_code <chr>, section <chr>,
## #   specialism_code <int>, activity_instance_id <chr>, .order <int>

Hospital Billing

hospital_billing
## Event log consisting of:
## 49951 events
## 288 traces
## 10000 cases
## 16 activities
## 49951 activity instances
## 
## # A tibble: 49,951 x 25
##    case_id activity lifecycle resource timestamp           actorange
##    <chr>   <fct>    <fct>     <fct>    <dttm>              <chr>    
##  1 A       NEW      complete  ResA     2012-12-16 19:33:10 <NA>     
##  2 A       FIN      complete  <NA>     2013-12-15 19:00:37 <NA>     
##  3 A       RELEASE  complete  <NA>     2013-12-16 03:53:38 <NA>     
##  4 A       CODE OK  complete  <NA>     2013-12-17 12:56:29 false    
##  5 A       BILLED   complete  ResB     2013-12-19 03:44:31 <NA>     
##  6 B       NEW      complete  ResA     2012-12-16 19:33:50 <NA>     
##  7 B       DELETE   complete  ResC     2013-10-19 12:37:05 <NA>     
##  8 C       NEW      complete  ResA     2013-01-13 21:04:24 <NA>     
##  9 C       FIN      complete  <NA>     2013-04-17 19:59:43 <NA>     
## 10 C       RELEASE  complete  <NA>     2013-04-18 02:30:35 <NA>     
## # ... with 49,941 more rows, and 19 more variables: actred <chr>,
## #   blocked <chr>, casetype <chr>, closecode <chr>, diagnosis <chr>,
## #   flaga <chr>, flagb <chr>, flagc <chr>, flagd <chr>, iscancelled <chr>,
## #   isclosed <chr>, msgcode <chr>, msgcount <int>, msgtype <chr>,
## #   speciality <chr>, state <chr>, version <chr>,
## #   activity_instance_id <chr>, .order <int>

Road Traffic Fine Management

traffic_fines
## Event log consisting of:
## 34724 events
## 44 traces
## 10000 cases
## 11 activities
## 34724 activity instances
## 
## # A tibble: 34,724 x 18
##    case_id activity  lifecycle resource timestamp           amount article
##    <chr>   <fct>     <fct>     <fct>    <dttm>               <dbl>   <int>
##  1 A1      Create F~ complete  561      2006-07-24 00:00:00   350.     157
##  2 A1      Send Fine complete  <NA>     2006-12-05 00:00:00    NA       NA
##  3 A100    Create F~ complete  561      2006-08-02 00:00:00   350.     157
##  4 A100    Send Fine complete  <NA>     2006-12-12 00:00:00    NA       NA
##  5 A100    Insert F~ complete  <NA>     2007-01-15 00:00:00    NA       NA
##  6 A100    Add pena~ complete  <NA>     2007-03-16 00:00:00   715.      NA
##  7 A100    Send for~ complete  <NA>     2009-03-30 00:00:00    NA       NA
##  8 A10000  Create F~ complete  561      2007-03-09 00:00:00   360.     157
##  9 A10000  Send Fine complete  <NA>     2007-07-17 00:00:00    NA       NA
## 10 A10000  Insert F~ complete  <NA>     2007-08-02 00:00:00    NA       NA
## # ... with 34,714 more rows, and 11 more variables: dismissal <chr>,
## #   expense <dbl>, lastsent <chr>, matricola <chr>,
## #   notificationtype <chr>, paymentamount <dbl>, points <int>,
## #   totalpaymentamount <chr>, vehicleclass <chr>,
## #   activity_instance_id <chr>, .order <int>