visualcomparisonofbusinessprocess flowcharts · visualcomparisonofbusinessprocess flowcharts...

Visual Comparison of Business ProcessFlowcharts

Bernhard Häussner

Julius-Maximilians-Universität WürzburgInstitut für Informatik

Lehrstuhl für Informatik IAlgorithmen, Komplexität und wissensbasierte Systeme

Advisors:Prof. Dr. Alexander Wolff

Fabian Lipp, M. Sc.

2018-03-18

What are Business Process Flowcharts?

hunger

bake

xor

black brown

eatsob

contentdone

Example for an event-driven process chain (EPC) as described byW.M.P. van der Aalst 1999. The process of making and

consuming pie.

Why? Motivation from industry needs

I Adaption of commercial off-the-shelf (COTS) software[Komplex-e]

I Workflows are documented, managed and compared as digitalbusiness process models. [de Moor and Delugach 2006]

I Merging organizational units

Automatic process model matching

I AI algorithms can give a similarity score [Dijkman et al. 2011]

I A process model matching contest yielded various results[Antunes et al. 2015]

I Results are never completely correct, making human visualcomparison necessary


I AI algorithms can give a similarity score [Dijkman et al. 2011]I A process model matching contest yielded various results

[Antunes et al. 2015]

I Results are never completely correct, making human visualcomparison necessary


I AI algorithms can give a similarity score [Dijkman et al. 2011]I A process model matching contest yielded various results

[Antunes et al. 2015]I Results are never completely correct, making human visual

comparison necessary

Business process flowcharts are graph drawings

I Business processes are basically graphs

I With nodes and edgesI Use graph drawing for layouting


I Business processes are basically graphsI With nodes and edges

I Use graph drawing for layouting


I Business processes are basically graphsI With nodes and edgesI Use graph drawing for layouting

Sugiyama [1981] graph drawing is suitable for businessprocess flowcharts

Five steps of layered graphdrawing:

I Cycle breakingI Layer assignmentI Vertex orderingI Horizontal positioningI Edge drawing

Visual graph comparisons are not easy

a

b

f

i

c

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g

h

A graph.

f g

a

bi

c

d

h

The same graph?

Can we also use graph comparisons?

I Not a whole lot of literature on visual graph comparison

I Biologists draw metabolic pathways, which are series ofchemical reactions. [Schreiber 2003]

I Merging of graphs with Semantic Graph Visualiser (SGV)[Andrews et al. 2009]

I New idea: Bringing vertices to the same height


I Not a whole lot of literature on visual graph comparisonI Biologists draw metabolic pathways, which are series of

chemical reactions. [Schreiber 2003]

I Merging of graphs with Semantic Graph Visualiser (SGV)[Andrews et al. 2009]




chemical reactions. [Schreiber 2003]I Merging of graphs with Semantic Graph Visualiser (SGV)

[Andrews et al. 2009]




chemical reactions. [Schreiber 2003]I Merging of graphs with Semantic Graph Visualiser (SGV)

[Andrews et al. 2009]I New idea: Bringing vertices to the same height

Bringing vertices to the same height

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4

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6 8 7

3′

1′

8′

4′ 2′ 7′

5′

6′

A graph with “constraints”between similar nodes


I Inserting space between layers

I Problem: Crossings of constraintsI Solution: select as many non crossing constraints as possibleI But how?


I Inserting space between layersI Problem: Crossings of constraints

I Solution: select as many non crossing constraints as possibleI But how?


I Inserting space between layersI Problem: Crossings of constraintsI Solution: select as many non crossing constraints as possible

I But how?


I Inserting space between layersI Problem: Crossings of constraintsI Solution: select as many non crossing constraints as possibleI But how?


1

23

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6 8 7

3′

1′

8′

4′ 2′ 7′

5′

6′

Two graphs with similarities


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6 8 7

3′

1′

8′

4′ 2′ 7′

5′

6′

Two graphs with similarities

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78

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742

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3

We only need to look at layers


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742

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3



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I We can only bring one oftwo crossing lines to thesame level

I Line crossings form aconflict graph

I Just need to find amaximum independent set

I NP complete?


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78

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742

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3


1 3 2 4

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5 6

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Conflict graph

Permutation graphs

I Permutation graphs [Even et al. 1972]I Vertices: elements of a permutationI Edges: pairs of elements that are reversed by the permutationI The conflict graphs are permutation graphs


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78

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742

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The permutation reads as 3, 1,8, 7, 4, 2, 5, 6

1 3 2 4

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5 6

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Permutation graph

Finding an independent set

I (Maximum) independent sets are (longest) increasingsubsequences

I Can be found in O(n log n) timeI Algorithm uses ideas from Aldous and Diaconis 1999 and

Kim 1990

Example

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78

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742

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3

The permutation reads as 3, 1,8, 7, 4, 2, 5, 6

1 3 2 4

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5 6

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Permutation graph

Other examples:3, 8, 7, 4, 5, 6, 1, 2

4, 2, 3, 1

Result

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6 8 7

3′

1′

8′

4′ 2′ 7′

5′

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The graphs adjusted accordingto the longest increasing

subsequence

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678

18

7

425

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3

The adjusted layers

Possible improvement: interpolation

Adjusted by adding space Adjusted by spreading to fillthe space

Another variant: adjusted scrolling

Evaluation

I A tool was developed using JUNG [O’Madadhain et al. 2005]and KIELER

I Includes Andrews et al.’s SGV comparison with merged graphsI Works on EPCs, including those from Komplex-e and the

2015 process model matching contest

Evaluation


I Includes Andrews et al.’s SGV comparison with merged graphs

I Works on EPCs, including those from Komplex-e and the2015 process model matching contest

Evaluation


I Includes Andrews et al.’s SGV comparison with merged graphsI Works on EPCs, including those from Komplex-e and the

2015 process model matching contest

Comparing the numbers

I SGV: height: -11% to +48%, on average +6%

I SGV: width: +38% to +258%, on average +128%I Height adjustment: height: +3% to 46%, on average +22%I Height adjustment: width: no change


I SGV: height: -11% to +48%, on average +6%I SGV: width: +38% to +258%, on average +128%

I Height adjustment: height: +3% to 46%, on average +22%I Height adjustment: width: no change


I SGV: height: -11% to +48%, on average +6%I SGV: width: +38% to +258%, on average +128%I Height adjustment: height: +3% to 46%, on average +22%

I Height adjustment: width: no change


I SGV: height: -11% to +48%, on average +6%I SGV: width: +38% to +258%, on average +128%I Height adjustment: height: +3% to 46%, on average +22%I Height adjustment: width: no change

User study

I Tested on two participants first

I Learnings were incorporated into a final questionnaire of42 questions

I Three different example processes were pickedI 13 participants (8 CS, 3 Econ., 2 others)

Result: slightly more generous answers for height adjustmentand adjusted scrolling vs. merged layout, but only smallsample size.

User study

I Tested on two participants firstI Learnings were incorporated into a final questionnaire of

42 questions

I Three different example processes were pickedI 13 participants (8 CS, 3 Econ., 2 others)


User study


42 questionsI Three different example processes were picked

I 13 participants (8 CS, 3 Econ., 2 others)Result: slightly more generous answers for height adjustmentand adjusted scrolling vs. merged layout, but only smallsample size.

User study


42 questionsI Three different example processes were pickedI 13 participants (8 CS, 3 Econ., 2 others)


Future Work

I Smart use of colors to highlight similar elements

I Extension of the longest increasing subsequence algorithm tothe weighted problem

I Improvement of constraint visualisationI n : m matchings

Future Work

I Smart use of colors to highlight similar elementsI Extension of the longest increasing subsequence algorithm to

the weighted problem

I Improvement of constraint visualisationI n : m matchings

Future Work


the weighted problemI Improvement of constraint visualisation

I n : m matchings

Future Work


the weighted problemI Improvement of constraint visualisationI n : m matchings

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