Digital and Knowledge Economy UG4/MSc Building an Ontology Slide - - PDF document

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Digital and Knowledge Economy

UG4/MSc Building an Ontology Slide Set 8

• Dr. Jessica Chen-Burger

Computer Science, MACS Heriot-Watt University

Y.J.ChenBurger@hw.ac.uk

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What is Process Mining?

 A young field arise more than a decade ago  A combined origin

– Computational intelligence and data mining – Process modelling and analysis

 Activities involved in PM

– To discover actual processes – To help analyse processes (e.g. by comparing process models and actual processes) – To help improve actual processes

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Why Process Mining? (1)

 To understand processes that actually

happened

 To compare actual processes with processes

that one thought to have been carried out

 To compare actual processes with standard

processes

 To understand who carried out the processes  To understand what resources are used/needed

by processes

 To understand where processes are been

carried out (location, organisation)

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Why Process Mining? (2)

 To streamline and improve actual

processes, e.g.

– To reduce cost – To speed up processes – To reduce redundancy – To discover/remove irregularities

 To create improved standard process

model

 To reuse process models

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PM Three Functions (re-cap) Three types of PM

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Event Log

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Three Main PM Functions

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Where to apply Process Mining?

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Sample Control-Flow Diagram 1

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Sample Control-Flow Diagram 2

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Sample Control-Flow Diagram 3

[Source: Celonis slides]

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The Event Log (re-cap)

[Source: Celonis slides]

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Event Logs

 May have to pull information from multiple

places, e.g.

– Database tables – Message logs – Mail archives – Transaction logs

 Making sense of pulled information and create

an integrated event log, inc.

– Activities that is temporal based – May include information flow – May include process flow – May include cost information – May include actor/role information – May include mechanism used in an activity

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Problems in Event Logs

 Incorrectness

– Errors in event logs – Assumed/recalled data, not always real data recorded

 Missing information

– Missing events – Sparse entries in variables (of events)

 Missing definition (semantics)

– Process and data level

 Need to preserve privacy and security

– E.g. healthcare or financial data – Do you need consent from the actor that information are being recorded and the way information is being used?

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Object Management Group Business Process Model and Notation

(BPMN not examinable)

And – parallel gateway XOR – exclusive gateway Loop

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Basic Process Flow Control

 And gateway (parallel)(and-split/join)

– All activities are executed – They can be executed in parallel, if running on a parallel machine/network

 Xor gateway (choice; exclusive gateway)(Xor-

split/join)

– Exactly one activity is executed

 Or gateway (inclusive gateway)(Or-split/join)

– At least one activity is executed; – If more than one activity is executed, they can be executed in parallel, if running on a parallel machine/network

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Process Mining Guidelines

 Event data should aim for high quality  Log extraction should be driven by questions  Basic process flow control should be supported

in the process model, i.e.

– and/or/xor gateway

 Events (stored in event logs) should be related to

elements in the control-flow and process model

 Models are abstractions of the reality that are

created to support certain goals

 Process mining is a continuous process

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Challenges - 1

 Find, merge and cleaning event data  Dealing complex event logs having diverse

characteristics, e.g.

– Different sizes in cases – Large amount of different types of events to handle – Incomplete real-world samples – Too low level of abstraction of events

 Create representative benchmarks  Dealing with concept drift

– the process is changing while being analysed

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Challenges - 2

 Avoid representational bias by selecting a

suitable process modelling language

– Can it represent all of the basic/important processes?

 Balancing between quality criteria, i.e.

– Fitness (show all links between PM and logs), – Simplicity (simple model) – Precision (no noise) – Generalisation (describe the domain, not just sample events) – Problems to capture real cases with low frequency

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Challenges - 3

 Cross-organisational mining, e.g.

– End-to-end process in a Supply Chain – Cloud computing – different organisations executing the same/similar processes while sharing experiences, knowledge or a common infrastructure, e.g. salesforce.com – organisations may learn from one another

 Provide operational support (real-time)

– Detect (and alert) – Predict - use historical data as guide – Recommend

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Challenges - 4

 Combine process mining with other types of

analysis, e.g.

– Operations management – Data mining (e.g. pattern discovery) – Predicting future (e.g. use simulation) – Visual analytics – automated analysis with interactive visualisation

 Improve usability for non-experts

– Support living process model, not a static one – Use user-friendly UI, hide complexity

 Improve understand-ability for non-experts

– Indication of data accuracy; – Support for results generated

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Celonis Tool Demo

 http://www.macs.hw.ac.uk/~yjc32/proje

ct/Teaching/DKE-2016-17/coursework-2/

– Demo 1 – Demo 2

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Exercise - 1

 What is process mining?  Why is process mining useful?  What are the main functions/types of process

mining?

 How process mining interact with software systems?  What sorts of results may be derived from process

mining?

 What are the challenges?  Given a real-world scenario, can you recommend a

process mining solution, e.g. based on the 3 functions?

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Exercise - 2

 The Lothian Bus wishes to have a better

understanding of their customers’ usage of their buses, in the interest of providing better services based on lower cost.

 They are interested in, e.g.

– Where most of the customers get on the bus and where they take off – When they take the bus – When is the peak time – Where and when the traffic is congested – Whether buses are on-time

 Recommend relevant process mining

techniques and explain why.

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References

 IEEE CIS Task Force on Process Mining,

Process Mining Manifesto, 2011: http://www.win.tue.nl/ieeetfpm/doku.p hp?id=shared:process_mining_manifesto

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Reference (not examinable)

• BPMN model: http://www.bpmn.org/
• Jon Espen Ingvaldsen and Jon Atle Gulla,

Model-Based Business Process Mining: https://scholar.google.com/citations?use r=lq5InSEAAAAJ&hl=en