Archiving and Publishing in Practice: Event logs Joos Buijs MSc 3TU.Datacentrum Symposium 2014 June 11, 2014

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Software as a

Service (SaaS)

431 403 municipalities Germany: +/-12.000 U.S.: +/-20.000

Find the Differences

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Our Solution

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Traditional Situation

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The CoSeLoG Vision

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Approach

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Conf Mod

software system

(process)model

eventlogs

modelsanalyzes

discovery

records events, e.g., messages,

transactions, etc.

specifies configures implements

analyzes

supports/controls

extension

conformance

“world”

people machines

organizationscomponents

business processes

Process Mining: From Observed Behavior to Process Models

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The data: An Event Log

patient activity timestamp doctor age cost 5781 make X-ray 23-1-2014@10.30 Dr. Jones 45 70.00 5541 blood test 23-1-2014@10.18 Dr. Scott 61 40.00 5833 blood test 23-1-2014@10.27 Dr. Scott 24 40.00 5781 blood test 23-1-2014@10.49 Dr. Scott 45 40.00 5781 CT scan 23-1-2014@11.10 Dr. Fox 45 1200.00 5833 surgery 23-1-2014@12.34 Dr. Scott 24 2300.00 5781 handle payment 23-1-2014@12.41 Carol Hope 45 0.00 5541 radiation therapy 23-1-2014@13.57 Dr. Jones 61 140.00 5541 radiation therapy 23-1-2014@13.08 Dr. Jones 61 140.00

… … … … … …

case id activity name timestamp other data resource

Slide by prof. Wil van der Aalst

Process discovery: What are we doing?

Conformance: Where do we deviate?

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Extension: Highlight reality on model

frequent execution paths

execution & waiting times

people collaborating

where models deviate from log

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Other views on behavior: Social Network

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Other views on behavior: Events over time

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Other views on behavior: Events over relative time

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Back to the CoSeLoG project

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Conf Mod

My data @ 3TU

• 5 event logs • Comparable processes • 2010 - 2014 • More than 4,000 cases and almost 200,000 events

• DOIs assigned, data uploaded soon

/ Architecture of Information Systems Group PAGE 16 13-6-2014

My data @ 3TU

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(My) data @ 3TU

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http://data.3tu.nl/repository/collection:event_logs

Why did I upload my data?

• Repeatable experiments (PhD thesis) • Validation of work • Visibility • Trustworthiness

• Share effort/data with colleagues • Good/rich data is hard to get

/ Architecture of Information Systems Group PAGE 20