bupaR Docs | Public Logs
Public logs
The eventdataR package contains several real-life and
artificial logs. Each can be loaded using the data()
function. The currently available logs are listed below.
Real-life data
Sepsis
This real-life event log contains events of sepsis cases from a hospital. Sepsis is a life threatening condition typically caused by an infection. One case represents the pathway through the hospital. The events were recorded by the ERP (Enterprise Resource Planning) system of the hospital. There are about 1000 cases with in total 15,000 events that were recorded for 16 different activities. Moreover, 39 data attributes are recorded, e.g., the group responsible for the activity, the results of tests and information from checklists. Events and attribute values have been anonymized. The time stamps of events have been randomized, but the time between events within a trace has not been altered.
Source: https://doi.org/10.4121/uuid:915d2bfb-7e84-49ad-a286-dc35f063a460
sepsis %>%
head()## # Log of 6 events consisting of:
## 1 trace
## 1 case
## 6 instances of 6 activities
## 3 resources
## Events occurred from 2014-10-22 11:15:41 until 2014-10-22 11:34:00
##
## # Variables were mapped as follows:
## Case identifier: case_id
## Activity identifier: activity
## Resource identifier: resource
## Activity instance identifier: activity_instance_id
## Timestamp: timestamp
## Lifecycle transition: lifecycle
##
## # A tibble: 6 × 34
## case_id activity lifec…¹ resou…² timestamp age crp diagn…³
## <chr> <fct> <fct> <fct> <dttm> <dbl> <dbl> <chr>
## 1 A ER Registrati… comple… A 2014-10-22 11:15:41 85 NA A
## 2 A Leucocytes comple… B 2014-10-22 11:27:00 NA NA <NA>
## 3 A CRP comple… B 2014-10-22 11:27:00 NA 210 <NA>
## 4 A LacticAcid comple… B 2014-10-22 11:27:00 NA NA <NA>
## 5 A ER Triage comple… C 2014-10-22 11:33:37 NA NA <NA>
## 6 A ER Sepsis Tri… comple… A 2014-10-22 11:34:00 NA NA <NA>
## # … with 26 more variables: diagnosticartastrup <lgl>, diagnosticblood <lgl>,
## # diagnosticecg <lgl>, diagnosticic <lgl>, diagnosticlacticacid <lgl>,
## # diagnosticliquor <lgl>, diagnosticother <lgl>, diagnosticsputum <lgl>,
## # diagnosticurinaryculture <lgl>, diagnosticurinarysediment <lgl>,
## # diagnosticxthorax <lgl>, disfuncorg <lgl>, hypotensie <lgl>, hypoxie <lgl>,
## # infectionsuspected <lgl>, infusion <lgl>, lacticacid <chr>,
## # leucocytes <chr>, oligurie <lgl>, sirscritheartrate <lgl>, Hospital Log
Real life log of a Dutch academic hospital, originally intended for use in the first Business Process Intelligence Contest (BPIC 2011).
Source: https://doi.org/10.4121/uuid:d9769f3d-0ab0-4fb8-803b-0d1120ffcf54
hospital %>%
head()## # Log of 6 events consisting of:
## 1 trace
## 1 case
## 6 instances of 4 activities
## 3 resources
## Events occurred from 2005-01-03 until 2005-01-05
##
## # Variables were mapped as follows:
## Case identifier: case_id
## Activity identifier: activity
## Resource identifier: group
## Activity instance identifier: activity_instance_id
## Timestamp: timestamp
## Lifecycle transition: lifecycle
##
## # A tibble: 6 × 98
## case_id activity lifec…¹ group timestamp CASE_…² CASE_…³ CASE_…⁴
## <chr> <fct> <fct> <fct> <dttm> <dbl> <dbl> <dbl>
## 1 00000000 1e consult… comple… Radi… 2005-01-03 00:00:00 33 NA NA
## 2 00000000 administra… comple… Radi… 2005-01-03 00:00:00 33 NA NA
## 3 00000000 verlosk.-g… comple… Nurs… 2005-01-05 00:00:00 33 NA NA
## 4 00000000 echografie… comple… Obst… 2005-01-05 00:00:00 33 NA NA
## 5 00000000 1e consult… comple… Nurs… 2005-01-05 00:00:00 33 NA NA
## 6 00000000 administra… comple… Nurs… 2005-01-05 00:00:00 33 NA NA
## # … with 90 more variables: `CASE_age:3` <dbl>, `CASE_age:4` <dbl>,
## # `CASE_age:5` <dbl>, CASE_diagnosis <chr>,
## # CASE_diagnosis_treatment_combination_id <dbl>,
## # `CASE_diagnosis_treatment_combination_id:1` <dbl>,
## # `CASE_diagnosis_treatment_combination_id:10` <dbl>,
## # `CASE_diagnosis_treatment_combination_id:11` <dbl>,
## # `CASE_diagnosis_treatment_combination_id:12` <dbl>, …Hospital Billing
The ‘Hospital Billing’ event log was obtained from the financial modules of the ERP system of a regional hospital. The event log contains events that are related to the billing of medical services that have been provided by the hospital. Each trace of the event log records the activities executed to bill a package of medical services that were bundled together. The event log does not contain information about the actual medical services provided by the hospital. The 100,000 traces in the event log are a random sample of process instances that were recorded over three years. Several attributes such as the ‘state’ of the process, the ‘caseType’, the underlying ‘diagnosis’ etc. are included in the event log. Events and attribute values have been anonymized. The time stamps of events have been randomized for this purpose, but the time between events within a trace has not been altered.
Source: https://doi.org/10.4121/uuid:76c46b83-c930-4798-a1c9-4be94dfeb741
hospital_billing %>%
head()## # Log of 6 events consisting of:
## 2 traces
## 2 cases
## 6 instances of 5 activities
## 3 resources
## Events occurred from 2012-12-16 19:33:10 until 2013-12-19 03:44:31
##
## # Variables were mapped as follows:
## Case identifier: case_id
## Activity identifier: activity
## Resource identifier: resource
## Activity instance identifier: activity_instance_id
## Timestamp: timestamp
## Lifecycle transition: lifecycle
##
## # A tibble: 6 × 25
## case_id activity lifecycle resource timestamp actor…¹ actred blocked
## <chr> <fct> <fct> <fct> <dttm> <lgl> <lgl> <lgl>
## 1 A NEW complete ResA 2012-12-16 19:33:10 NA NA FALSE
## 2 A FIN complete <NA> 2013-12-15 19:00:37 NA NA NA
## 3 A RELEASE complete <NA> 2013-12-16 03:53:38 NA NA NA
## 4 A CODE OK complete <NA> 2013-12-17 12:56:29 FALSE FALSE NA
## 5 A BILLED complete ResB 2013-12-19 03:44:31 NA NA NA
## 6 B NEW complete ResA 2012-12-16 19:33:50 NA NA FALSE
## # … with 17 more variables: casetype <chr>, closecode <chr>, diagnosis <chr>,
## # flaga <lgl>, flagb <lgl>, flagc <lgl>, flagd <lgl>, iscancelled <lgl>,
## # isclosed <lgl>, msgcode <chr>, msgcount <dbl>, msgtype <chr>,
## # speciality <chr>, state <chr>, version <chr>, activity_instance_id <chr>,
## # .order <int>, and abbreviated variable name ¹actorangeRoad Traffic Fine Management
Real-life event log of an information system managing road traffic fines.
Source: https://doi.org/10.4121/uuid:270fd440-1057-4fb9-89a9-b699b47990f5
traffic_fines %>%
head()## # Log of 6 events consisting of:
## 2 traces
## 2 cases
## 6 instances of 4 activities
## 2 resources
## Events occurred from 2006-07-24 until 2007-03-16
##
## # Variables were mapped as follows:
## Case identifier: case_id
## Activity identifier: activity
## Resource identifier: resource
## Activity instance identifier: activity_instance_id
## Timestamp: timestamp
## Lifecycle transition: lifecycle
##
## # A tibble: 6 × 18
## case_id activity lifec…¹ resou…² timestamp amount article dismi…³
## <chr> <fct> <fct> <fct> <dttm> <chr> <dbl> <chr>
## 1 A1 Create Fine comple… 561 2006-07-24 00:00:00 35.0 157 NIL
## 2 A1 Send Fine comple… <NA> 2006-12-05 00:00:00 <NA> NA <NA>
## 3 A100 Create Fine comple… 561 2006-08-02 00:00:00 35.0 157 NIL
## 4 A100 Send Fine comple… <NA> 2006-12-12 00:00:00 <NA> NA <NA>
## 5 A100 Insert Fin… comple… <NA> 2007-01-15 00:00:00 <NA> NA <NA>
## 6 A100 Add penalty comple… <NA> 2007-03-16 00:00:00 71.5 NA <NA>
## # … with 10 more variables: expense <chr>, lastsent <chr>, matricola <dbl>,
## # notificationtype <chr>, paymentamount <dbl>, points <dbl>,
## # totalpaymentamount <chr>, vehicleclass <chr>, activity_instance_id <chr>,
## # .order <int>, and abbreviated variable names ¹lifecycle, ²resource,
## # ³dismissalArtifical 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.
patients %>%
head()## # Log of 6 events consisting of:
## 1 trace
## 6 cases
## 6 instances of 1 activity
## 1 resource
## Events occurred from 2017-01-02 11:41:53 until 2017-01-04 16:07:47
##
## # Variables were mapped as follows:
## Case identifier: patient
## Activity identifier: handling
## Resource identifier: employee
## Activity instance identifier: handling_id
## Timestamp: time
## Lifecycle transition: registration_type
##
## # A tibble: 6 × 7
## handling patient employee handling_id registr…¹ time .order
## <fct> <chr> <fct> <chr> <fct> <dttm> <int>
## 1 Registration 1 r1 1 start 2017-01-02 11:41:53 1
## 2 Registration 2 r1 2 start 2017-01-02 11:41:53 2
## 3 Registration 3 r1 3 start 2017-01-04 01:34:05 3
## 4 Registration 4 r1 4 start 2017-01-04 01:34:04 4
## 5 Registration 5 r1 5 start 2017-01-04 16:07:47 5
## 6 Registration 6 r1 6 start 2017-01-04 16:07:47 6
## # … with abbreviated variable name ¹registration_typePatients activitylog
Equivalent process log of patient, but stored as an activity log.
patients_act %>%
head()## # Log of 12 events consisting of:
## 1 trace
## 6 cases
## 6 instances of 1 activity
## 1 resource
## Events occurred from 2017-01-02 11:41:53 until 2017-01-04 20:07:50
##
## # Variables were mapped as follows:
## Case identifier: patient
## Activity identifier: handling
## Resource identifier: employee
## Timestamps: start, complete
##
## # A tibble: 6 × 7
## handl…¹ patient emplo…² handl…³ .order complete start
## <fct> <chr> <fct> <chr> <int> <dttm> <dttm>
## 1 Regist… 1 r1 1 1 2017-01-02 12:40:20 2017-01-02 11:41:53
## 2 Regist… 2 r1 2 2 2017-01-02 15:16:38 2017-01-02 11:41:53
## 3 Regist… 3 r1 3 3 2017-01-04 06:36:54 2017-01-04 01:34:05
## 4 Regist… 4 r1 4 4 2017-01-04 04:25:06 2017-01-04 01:34:04
## 5 Regist… 5 r1 5 5 2017-01-04 20:07:50 2017-01-04 16:07:47
## 6 Regist… 6 r1 6 6 2017-01-04 18:12:46 2017-01-04 16:07:47
## # … with abbreviated variable names ¹handling, ²employee, ³handling_id
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