Presentation of the paper: Role-Activity Diagrams Modeling Based on Workflow Mining WeiDong Zhao; Weihui Dai; Anhua Wang; Xiaochun Fang Computer Science and Information Engineering, 2009 WRI World Congress on , vol.4, no., pp.301,305, March 31 2009-April 2 2009 DOI: 10.1109/CSIE.2009.992

1. Role-activity Diagrams Modeling
Based on Workflow Mining
2009 World Congress on Computer Science and Information Engineering
Weidong Zhao, Anhua Wang, Xiaochun Fang @ Software School, Fudan University, Shanghai, China
Weihui Dai @ Management School, Fudan University, Shanghai, China
Presentation by Onur Yılmaz - onur@onuryilmaz.me

2. Outline
 Introduction
 Basic Concepts
 Role Mining
 Conclusions

3. Introduction
Role Activity Diagram (RAD)  a basic role-oriented process model
Process
Models
Activity-based
Process Models
Role-oriented
Process Models

4. Introduction
Describe business processes as
actors and their interactions from the
organization perspective
Role-oriented
Process Models

5. Introduction
 Adapted from cross-functional
process models
 Using sub-processes to describe
process roles’ responsibility
 So as to highlight the interaction
between roles
Role-activity
diagrams (RAD)

6. Introduction
 RAD requires a deep knowledge
of processes and organizational
model so as to identify roles.
Role-activity
diagrams (RAD)

7. Introduction
 Workflow management systems
produce lots of logs
 Process mining can reconstruct
process models from real
workflow logs
 Thus workflow mining may be a
more objective method for role
identification
Workflow Mining

8. Introduction
•This paper is based on hypotheses:
• Actors playing the same role have similar duties, abilities and
characteristics
• Activities performed by these actors stand for their work
• So roles can be identified by discovering actors with similar work from
workflow logs

9. Introduction
Existing Methods
 α algorithm can mine the WF-net
 the dependence between activities
 Organizational mining
 actors are the center of business processes and social networks can be drawn
out by analyzing business relations among actors

10. Introduction
Existing Methods
 Role engineering
 the role-mining tool ORCA aggregates permissions bottom-up
into a role hierarchy using clustering analysis interactively
with the aid of business experts

11. Introduction
What is presented?
 Workflow mining is used for role identification
taking the work similarity of actors as a criterion
 Role mining, the interaction between roles are
analyzed through social network diagrams among
actors, and finally role-activity diagrams is mined.

12. Basic Concepts
Set of all activities in workflow logs
A = {a1, a2,…, am}
m = |A| is the number of activities in workflow logs

13. Basic Concepts
Set of all process actors
P = {p1, p2,…, pn}
where n is the number of actors

14. Basic Concepts
 Set of all workflow instances in logs I
 and for any workflow instance i ∈ I, i= (a1 a2 … ak),
 AS(i) is the set of activities in the instance i
 sequence of activities a1 a2 … ak represents the actual
execution ordering.

15. Basic Concepts
Activity b depends on activity a, a>b
If
such that
According to definition, a>b means that activity b is executed after
activity a and there exists no other activities between.

16. Basic Concepts
Activity b depends on activity a directly (direct dependence)
if for each workflow instance i ∈ I, there only exists a>b but not b>a
Dependence between activity a and b is consistent in all workflow
instances. It hints that there exists state transition from activity a to
b.

17. Basic Concepts
Given I, we can find all the activity pairs, which accord with the direct
dependence.
The activity pairs is denoted as DEP

18. Basic Concepts
Clothing production system
a inquiry and quoting
b contract signing
c prototype designing
d fabric requiring
e fabric drawing
f fabric purchasing
g fabric processing

19. Basic Concepts
6 workflow instances
i1 = {abcg},
i2 = {abdecg},
i3 = {abcdeg},
i4= {abdeg},
i5 = {abdceg},
i6 = {abdfecg}
WF-net model using the α algorithm

20. Basic Concepts
DEP of the clothing production
workflow
{(a, b), (a, c), (a, d), (a, e), (a, f), (a, g),
(b, c), (b, d), (b, e), (b, f), (b, g), (c, g),
(d, e), (d, f), (d, g), (e, g),(f, e), (f, g)}
WF-net model using the α algorithm

21. Basic Concepts
Adjacent activity set adjAS
where S and Av are two activity sets
For any activity in adjAS(b), it belongs to Av but not S, and there
exists dependence between the activity and other activities in S

22. Basic Concepts
In this paper, roles are identified by the ratio of the times actors
executing each activity to the total times of these actors executing all
activities
total of pi executing
related activities
times(pi, aj) is the times of
pi executing aj
Tom 100 times in total, in which “Fabric requiring” is executed 30 times, thus
R(Tom, Fabric requiring) = 0.3

23. Basic Concepts
Vector of activity execution in the work of the actor pi
S(pi, Au)=(R(pi, a1), R(pi, a2),…,R(pi, ak))
k-dimension vector of activities the actor pi takes charge of
For example,
R(Tom, fabric requiring)=0.3
R(Tom, fabric checkout) = 0.4
R(Tom, production inspection) = 0.05,
vector of Tom (0.3, 0.4, 0.05)

24. Basic Concepts
Difference degree of activity set Au
average difference of activity execution by the actors.
Larger difference degree means more difference between actors in
their work.
In this paper, the difference degree is used to identify process roles.

25. Times of activities from workflow logs
Basic Concepts
Example

26. Percentages of activities
Basic Concepts
Example

27. Percentages of activities
S(p101, {a}) = (0.625),
S(p107, {a}) = (0.533)
AG({a}) = (0.625 + 0.533)/2 = 0.579
Basic Concepts
Example

28. Percentages of activities
Difference degree of {a, b}
S(p101, {a, b}) = (0.625, 0.375),
S(p107, {a,b}) = (0.533, 0.466),
S(p115, {a, b}) = (0, 0.277)
AG({a, b})
= ( (0.625 + 0.533) /3, (0.375 + 0.466 + 0.277)/3 )
= (0.386, 0.373)
D({a, b}) = 0.27
Basic Concepts
Example

29. Role Mining
 It is assumed that
 Actors who play the same role are responsible for the sub-
process (activity set) whose
difference degree is less than the predefined threshold T

30. Role Mining
Mining the activity set executed by each role
 Discover sub-processes in which
activities are executed by actors
playing the same roles

31. Input:
 the activity set A,
 dependence set DEP
 threshold T
Output:
 sub-processes
corresponding to
each role

32. If 1 is left
Select the smallest
difference degree
Adjacent activity
set from dependent
ones
Add if not
exceeding the
threshold

33. {a} has the least
dependence degree
D({a}) = 0.046
adjAS(a) = {b}
activity b is added
and D({a, b}) = 0.27
Example
Threshold T= 0.33
the adjacent activity
set of {a, b}  {c, d}
D({a, b, c}) = 0.345
D({a, b, d}) = 0.379
Both larger than T.
Roles: {a, b}

34. {d} has the least
dependence degree
D({d}) = 0.051
adjAS(d) = {c, e, f}.
activity c is added
and D({d, c})=0.164
e is added and
D({d, c, e})=0.219
d→f and f→e,
f is added to the
activity set for
principle of order
preserving.
Roles: {a, b}, {d, c, e, f}
Example
Threshold T= 0.33

35. {g} is the only remainder
Roles: {a, b}, {d, c, e, f}, {g}
Example
Threshold T= 0.33

36. Role Mining
Mining the activity set executed by each role
{a,b}
{a,b}
{a,b}
{d,c,e,f}
{d,c,e,f}
{d,c,e,f}
{d,c,e,f}
{g}
{g}
{g}

37. RAD Modeling
 Activity set taken by each role makes up sub-processes in
RAD modeling and the sub-processes
 Can be identified by presented algorithm
 In this paper, the interaction between roles based on social
network analysis is modeled.

38. RAD Modeling
 Activity dependence between process actors pi, pj is denoted as
 rel(pi, pj) = {(a, b)|i ∈ I, i = (a1a2…a b…ak), pi, pj ∈ P,
 a is executed by pi,
 b is executed by pj , and a → b.
 Interaction between roles based on the activity dependence
between actors.

39. RAD Modeling
 If there exists direct dependence between activity a and b, and
in a workflow instance, activity a is executed by the actor pi and
activity b is executed by actor pj, then the activity pair (a, b)
shows that pj depends on pi.
Person pi Role Ri
Role Rj
Activity ap
Activity aq
Assigned
Assigned
Responsible
Responsible
Dependence
(From workflow log)
Person pj

40. RAD Modeling
 Example:
p105
Planning
Manager
Technician
b
c
Responsible
Responsible
b  c
p115
In RAD modeling
connection(planning manager, technician) = {b}
is found

41. RAD Modeling
 Example:
a
b
c
d
g
f

42. RAD Modeling
Threshold Values
 By comparison, it seems that we can get better role identification
results when T is set between 0.3 and 0.4
 It needs further probative work

43. Conclusion
 How to identify roles and their interactions is necessary
for RAD modeling but most of methods for addressing
the issue seem to be subjective
 In this paper, workflow mining is used to discover process
roles

44. Conclusion
Future Work
 Threshold T is not easy to choose
 More research should be done to mine workflow models
with the loop-structure

45. References
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[6] Wil M.P V, Song M(1998). Discovering models of software processes from event-based data], ACM Transactions
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Process Management,pp244-260
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control models and technologies. Stockholm, Sweden: SACMAT，pp168-176
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Information Systems, vol.28,no.6,pp505-532

46. Role-activity Diagrams Modeling
Based on Workflow Mining
2009 World Congress on Computer Science and Information Engineering
Weidong Zhao, Anhua Wang, Xiaochun Fang @ Software School, Fudan University, Shanghai, China
Weihui Dai @ Management School, Fudan University, Shanghai, China
Presentation by Onur Yılmaz - onur@onuryilmaz.me