…It has been more than 10 years since a strong research stream on services started from the field of computer science. The main trigger was without a doubt the introduction of the Web Service Description Language (WSDL), a specification to represent a piece of software functionally which could be remotely invoked. Nonetheless, this was only the “tipping point”. The generalized interest on this new development was followed by interesting topics of research on the application of semantics to enhance the description of services, the composition of services into processes, the analysis of the quality of services, the complexity of processes supporting services, and the development of comprehensive service description languages. This seminar will provide an overview of the main research topics around services and will glimpse at a new research field on the analysis of service networks...

1. Ten years of service research from
a computer science perspective
Jorge Cardoso
CISUC/Dept. Informatics Engineering, University of Coimbra, Portugal
Karlsruhe Service Research Institute, Karlsruhe Institute of Technology, Germany
jorge.cardoso@kit.edu; jcardoso@dei.uc.pt
Departamento de Engenharia Informática
FCTUC FACULDADE DE CIÊNCIAS E TECNOLOGIA da UNIVERSIDADE DE COIMBRA

2. Abstract
…It has been more than 10 years since a strong research stream on services started from
the field of computer science. The main trigger was without a doubt the introduction of
the Web Service Description Language (WSDL), a specification to represent a piece of
software functionally which could be remotely invoked. Nonetheless, this was only the
“tipping point”. The generalized interest on this new development was followed by
interesting topics of research on the application of semantics to enhance the description
of services, the composition of services into processes, the analysis of the quality of
services, the complexity of processes supporting services, and the development of
comprehensive service description languages. This seminar will provide an overview of
the main research topics around services and will glimpse at a new research field on the
analysis of service networks...
Karlsruhe, 15 Jun 2013
Jorge Cardoso
11/1/2013
Ten years of service research from a computer science perspective
2

3. Semantic Web Services
11/1/2013
Semantic Web Services
Service Descriptions
Quality of Service
Process Complexity
Internet of Services
Service Networks
Ten years of service research from a computer science perspective
3

4. A simple problem to solve
Request message
010101110100101
Response message
0101001011101001
Client
11/1/2013
Internet
Ten years of service research from a computer science perspective
Server
4

5. Almost 15 years to “Solve”
•
•
•
•
•
•
Web services (WSDL/SOAP)
Java Remote Method Invocation (Java RMI)
Distributed Component Object Model (DCOM)
Common Object Request Broker Architecture (CORBA)
Remote Procedure Calls (RPC)
Socket Programming (SP)
SUN RPC (1985)
24.04.2013
CORBA (1992)
DCOM (1996)
JAVA RMI (1996)
Service Oriented Computing II – SS 2013
Berkeley SP (1983)
WSDL/SOAP (2000)

6. The Problem (2000)
The web
Intraorganizational
Response message
0101001011101001
11/1/2013
Request message
010101110100101
Ten years of service research from a computer science perspective
6

7. The Search & Matching Problem
?
?
?
11/1/2013
Ten years of service research from a computer science perspective
7

8. Previous Approaches
• Keyword-based
• Information Retrieval
Techniques
11/1/2013
Ten years of service research from a computer science perspective
8

9. The Idea (2002)
Ontology with background
knowledge
?
?
?
Cardoso, J. and Sheth, A. Semantic e-Workflow Composition. In Journal of
Intelligent Information Systems (JIIS), Vol. 21 (3): 191-225, 2003.
11/1/2013
Semantic Matching
Ten years of service research from a computer science perspective
9

10. Example of an ontology
11/1/2013
Ten years of service research from a computer science perspective
10

11. Semantic Descriptions
• Web Service Technology
Ontology
– Automated
discovery, selection, compositio
n,
– Web-based execution of
services
• Semantic Web Technology
– Allow machine supported data
interpretation
– Ontologies as data model
• Semantic Web Services
– as integrated solution for
realizing the vision of the next
generation of the Web
11/1/2013
WSDL
Ten years of service research from a computer science perspective
11

12. Semantic Matching = Ontology
Similarity ?
Concepts from the same Ontology
a) Concepts are the same (O=I)
b) Concept I subsumes concept O (O>I)
c) Concept O subsumes concept I (O<I), or
d) Concept O is not directly related to concept I
(O I).
CalendarDate
…
A1
Event
…
…
Web Service
Web Service
ST1,2 (output)
SO1,2,3,4 (input)
Time ontology
b)
Time ontology
Temporal-Entity
Time
Interval
Time
Domain
Temporal-Entity
Time-Point
{absolute_time}
a)
Time
Interval
2
Time
Domain
Time-Point
1
{year, month, day}
Car subsumes 2-Wheel drive
Date
{absolute_time}
1
Time
{hour, minute, second}
{year, month, day}
Event
Calendar-Date
{dayOftheWeek, monthOftheYear}
c)
Scientific-Event
Time
Date
3
2
Calendar-Date
A2
{hour, minute, second}
4
Event
{dayOftheWeek, monthOftheYear}
{millisecond}
Scientific-Event
{millisecond}
d)
11/1/2013
Ten years of service research from a computer science perspective
12

13. Semantic Matching <> Ontology
1,
SemS ' (O, I )
O
I
1,
O
| p (O ) |
,
O
| p( I ) |
Similarity' (O, I ), O
I
I subsumes O
I
O subsumes I
I
O has no subsumes
relation with I
(Remember)
Car subsumes 2-Wheel drive
similarity' (O, I )
| p(O)
| p(O)
p( I ) | | p(O) p( I ) |
*
p( I ) |
| p( I ) |
p(X) = properties of X
Based on Tversksy (1977)
feature model
Cardoso, J. Discovering Semantic Web services with and without a Common Ontology Commitment. In The 3rd
International Workshop on Semantic and Dynamic Web Processes (SDWP 2006),
11/1/2013
Ten years of service research from a computer science perspective
13

14. Other aspects to match
Similarity ?
• Quality of Service
A1
CalendarDate
Event
…
…
A2
…
Web Service
Web Service
1
SynNS ( R.sn, ADV.sn)
2
1
SynSimilarty( R, ADV )
2
OpSimilarity(R, ADV )
3
SynDS( R.sd , ADV.sd )
and
1
,
2
[0..1],
[0..1]
QoSdimD( R, ADV , time) * QoSdimD( R, ADV , cost ) * QoSdimD( R, ADV , reliability)
OpSimilarity(R, ADV )
3
QoSdimD( R, ADV , time) * QoSdimD( R, ADV , cost ) * QoSdimD( R, ADV , reliability)
QoSdimD(R, ADV , dim)
Cardoso, J.; Miller, J. A.; Sheth, A.; Arnold, J. and
Kochut, K. Quality of service for workflows and web
service processes. In Journal of Web Semantics, Vol. 1
(3): 281-308, 2004.
11/1/2013
3
dcdmin ( R, ADV , dim) * dcdavg ( R, ADV , dim) * dcdmax( R, ADV , dim)
dcd m in ( R, ADV , dim) 1
| min( ADV .qos(dim)) min( R.qos(dim)) |
min( R.qos(dim))
Ten years of service research from a computer science perspective
14

15. Another matching problem…
10000 *
11/1/2013
Ten years of service research from a computer science perspective
15

16. The (same) Idea
Ontology with background
knowledge
?
?
?
Cardoso, J. and Sheth, A. Semantic e-Workflow Composition. In Journal of
Intelligent Information Systems (JIIS), Vol. 21 (3): 191-225, 2003.
11/1/2013
Semantic Matching
Ten years of service research from a computer science perspective
16

17. Semantic Process Composition
0.76
0.14
0.98
ADV2
ADV1
0.31 0.68
ADV3
Match Function
0.43
Conference Registry
Service
Process
0.34
0.74
f(R, ADV1)
0.99
f(R, ADV2)
?
f(R, ADV3)
Hotel Reservation
Service
Date
Date
Duration
Duration
City
City
Conference
Start
Get
Conference
Information
A
Employee ID
11/1/2013
User Name
User Name
Address
Address
Itinerary
Itinerary
B
ST
R
Travel
Reservation
End
Hotel
Reservation
Get User
Information
Ten years of service research from a computer science perspective
17

18. Semantic Web Services
•
•
•
•
Cardoso, J. The Semantic Web Vision: Where Are We?. In IEEE Intelligent Systems, Vol. 22 (5): 8488, 2007.
Cardoso, J. The Semantic Web: A mythical story or a solid reality. In Metadata and Semantics, pages 253257, Springer, Heidelberg, 2008.
Cardoso, J.; Miller, J. A. and Emani, S. Tutorial Lectures: Web Services Discovery Utilizing Semantically
Annotated WSDL. In 4th International Summer
Patterson, R.; Miller, J. A.; Cardoso, J. and Davis, M. Bringing Semantic Security to Semantic Web
Services. In The Semantic Web: Real-World
11/1/2013
Ten years of service research from a computer science perspective
18

19. Semantic Web Services
11/1/2013
Semantic Web Services
Service Descriptions
Quality of Service
Process Complexity
Internet of Services
Service Networks
Ten years of service research from a computer science perspective
19

20. Remember our problem…
Service Description
We were looking for
apples
Web Services
(…a procedure or function…)
11/1/2013
Service
Endpoint
Binding
Interface
Operation
Types
Ten years of service research from a computer science perspective
20

21. What about more complex services?
From
apples
to more
complex
fruits
11/1/2013
Ten years of service research from a computer science perspective
21

22. In other words
WEB-BASED SERVICES
HUMAN-COMPUTER INTERACTION
USER INTERFACE
CUSTOMER EXPERIENCE
TYPE II
CLOUD SERVICES
Complex interfaces
Dependencies between calls
Pricing, legal aspects, SLA
SOAP, REST, etc.
WEB SERVICES
TYPE I
COMPLEXITY
TYPE III
INTERNET/WEB-BASED SELF-SERVICE TECHNOLOGY
(I/W-SST)
11/1/2013
Simple invocations
Simple atomic, singular services
Intra-organizations
Machine-machine interaction
Ten years of service research from a computer science perspective
22

23. The Idea (2008)
Made for c omputers (S O A)
Addres s
P ort
Arguments
D ata type
…
T ec hnic al
WS DL
Made for people (IoS )
P rotocols
P rovider
Addres s
C ons umer
P orts
B undling
B
T ec hnic al
…
Marketing us ines s
US DL
L egal
…
O perational O perations
F unctionality
R es ources
…
Cardoso, J. Service Engineering for Future Business Value Networks. In Tenth International Conference on Enterprise Information
Systems (ICEIS 2008), pages 15-20, Barcelona, Spain, ISBN: 978-989-8111-37-1, 2008.
11/1/2013
Ten years of service research from a computer science perspective
23

24. Services Description (2009-13)
C
P
C
P
P
P
C
P
C
P
C
P
P
C
C
C
P
P
P
P
C
P
C
P
P
* advertise and discover P
services
* selection, composition
and interoperation of
services
11/1/2013
C
C
Cardoso, J.; Barros, A.; May, N. and Kylau, U. Towards a Unified
Service Description Language for the Internet of Services:
Requirements and First Developments. In IEEE International
Conference on Services Computing, 2010.
Ten years of service research from a computer science perspective
24

25. USDL:INTERACTIONPOINT C
•
Blueprint
–
•
line of interaction
E.g. face-to-face actions between
employees and customers
NAME:
usdl:InteractionPoint
DESCRIPTION:
rdfs:comment """<p>An InteractionPoint represents an actual step in accessing and performing
operations of the service. On a technical level this could translate into calling a Web Service
operation.
On a professional level, it could mean that consumer and provider meet in person to exchange
service parameters or resources involved in the service delivery (e.g. documents that are processed
by the provider).
An InteractionPoint can be initiated by the consumer or the provider. Since InteractionPoints may
take time and have an ordering with respect to other InteractionPoints, this is a subclass of
TimeSpanningEntity. One can therefore express temporal relationships between InteractionPoints
such as before or after. For richer expressions the time ontology constructs could be
used.</p>"""@en .
SUBCLASS:
rdfs:subClassOf usdl:TimeSpanningEntity;
22.05.2013
Service Oriented Computing II – SS 2013

26. Resources
http://www.linked-usdl.org/
11/1/2013
https://github.com/linked-usdl/
Ten years of service research from a computer science perspective
26

27. History
•
a-USDL/2009
– Initial version of USDL [CBM+2010] ready in 2009.
– Later renamed to a-USDL (pronounced alpha-USDL).
– http://www.genssiz.org/research/service-modeling/alpha-usdl/
•
USDL/2011
– A W3C Incubator group was created USDL was adapted and extended
based on industry feedback at the end of 2011.
– http://www.w3.org/2005/Incubator/usdl/
•
Linked-USDL/2012--?
– In order to make the specification gain a wider acceptance, a version
called Linked USDL emerged using Semantic Web principles. Its
development is still in progress.
– http://linked-usdl.org/
Cardoso, J.; Winkler, M. and Voigt, K. A Service Description Language for the Internet of Services. In First International Symposium on Services
Science (ISSS'09), Leipzig, Germany, ISBN: 978-3-8325-2169-1, 2009.
11/1/2013
Ten years of service research from a computer science perspective
27

28. Applications
Consider cost, compatibility, space, speed, etc.
API
Cloud Services
Decision Maker
11/1/2013
Ten years of service research from a computer science perspective
28

29. Service Descriptions
•
•
•
•
•
Cardoso, J.; Binz, T.; Breitenbucher, Uwe; Kopp, O. and Leymann, F. Cloud Computing Automation:
Integrating USDL and TOSCA. In CAiSE, Springer, LNCS, Vol. , 2013.
Cardoso, J. and Miller, J. A Internet-Based Self-Services: from Analysis and Design to Deployment. In The
2012 IEEE International Conference on Services Economics (SE 2012), IEEE Computer
Society, Hawaii, USA, 2012.
Cardoso, J.; Barros, A.; May, N. and Kylau, U. Towards a Unified Service Description Language for the
Internet of Services: Requirements and First Developments. In IEEE International Conference on Services
Computing, IEEE Computer Society Press, Florida, USA, 2010.
Cardoso, J.; Voigt, K. and Winkler, M. Service Engineering for The Internet of Services. In Enterprise
Information Systems, pages 15-27, Springer, ISBN: 978-3-642-00669-2 (Print) 978-3-642-00670-8
(Online), 2009.
Cardoso, J.; Winkler, M. and Voigt, K. A Service Description Language for the Internet of Services. In First
International Symposium on Services Science (ISSS'09), Leipzig, Germany, ISBN: 978-3-8325-21691, 2009.
11/1/2013
Ten years of service research from a computer science perspective
29

30. Semantic Web Services
11/1/2013
Semantic Web Services
Service Descriptions
Quality of Service
Process Complexity
Internet of Services
Service Networks
Ten years of service research from a computer science perspective
30

31. Does this slide look familiar !?
-- 17 --
The Problem
How to evaluate the Quality of Service?
0.76
0.14
ADV2
ADV1
0.31 0.68
0.98
0.43
Conference Registry
Service
0.34
0.74
f(R, ADV1)
Process
ADV3
Match Function
Hotel Reservation
Service
0.99
f(R, ADV2)
?
f(R, ADV3)
Date
Date
Duration
Duration
City
City
Conference
Start
Get
Conference
Information
A
Employee ID
11/1/2013
User Name
User Name
Address
Address
Itinerary
Itinerary
B
ST
R
Travel
Reservation
End
Hotel
Reservation
Get User
Information
Ten years of service research from a computer science perspective
31

32. The Problem
How to evaluate the Quality of Service?
Send Report
t6
xor
xor
t1
Prepare
Sample
t2
Prepare
Clones
xor
t3
Sequencing
xor
t4
t5
Sequence
Processing
Create
Report
and
and
t8
Send
Bill
t7
How much does it costs?
How much time does it take?
How reliable it is?
11/1/2013
Ten years of service research from a computer science perspective
Store
Report
32

33. The Idea (2002)
p4
QoS
Send Report
t6
p1
p3
xor
xor
t1
Prepare
Sample
t2
Prepare
Clones
xor
p2
t3
Sequencing
xor
t4
Sequence
Processing
p5
t5
and
and
Create
Report
t8
Send
Bill
t7
Store
Report
QoS
Time
Cost
Reliability
Fidelity
QoS
QoS
QoS
QoS
QoS
QoS
Cardoso, J.; Miller, J. A.; Sheth, A.; Arnold, J. and Kochut, K. Quality of service for workflows and web service processes. In Journal of
Web Semantics, Vol. 1 (3): 281-308, 2004.
11/1/2013
Ten years of service research from a computer science perspective
33

34. Research Questions
• Specification
– What dimensions need to be part of the QoS model for processes?
• Computation
– What methods and algorithms can be used to compute, analyze, and
predict QoS?
• Monitoring
– What kind of QoS monitoring tools need to be developed?
• Control
– What mechanisms need to be developed to control processes, in
response to unsatisfactory QoS metrics?
11/1/2013
Ten years of service research from a computer science perspective
34

35. QoS Estimation
a)
QoSDim(t)
Designer AverageDim(t)
b)
QoSDim(t)
wi1* Designer AverageDim(t) + wi2* Multi-Workflow
AverageDim(t)
c)
QoSDim(t, w)
wi1* Designer AverageDim(t) + wi2* Multi-Workflow
AverageDim(t) + wi3*Workflow AverageDim(t, w)
d)
QoSDim(t, w, i)
wi1* Designer AverageDim(t) + wi2* Multi-Workflow
AverageDim(t) + wi3* Workflow AverageDim(t, w) + wi4*
Workflow AverageDim(t, w)
Instance Workflow AverageDim(t,w, i)
Designer AverageDim(t)
Average specified by the designer in the basic
class for dimension Dim
Multi-Workflow AverageDim (t)
Average of the dimension Dim for task t
executed in the context of any workflow
Average of the dimension Dim for task t
executed in the context of any instance of
workflow w
QoS dimensions computed at runtime
Instance AverageDim(t, w, i)
Runtime, design time,
between workflows, instances, etc.
Min value
Time
Cost
Reliability
Fidelity.ai
0.291
0
0.63
Basic class
Avg value
0.674
0
100%
0.81
Average of the dimension Dim for task t
executed in the context of instance i of
workflow w
Designer, multi-workflow, workflow and instance average
Max value
0.895
0
0.92
Distributional class
Dist. Function
Normal(0.674, 0.143)
0.0
1.0
Trapezoidal(0.7,1,1,4)
Task QoS for an automatic task (SP FASTA task)
11/1/2013
Ten years of service research from a computer science perspective
35

36. QoS Reduction Rules
Sequential
Parallel
Conditional
Loop
Fault-tolerant
Network
t2
(a)
tn
+
pon
tb
ta
p1n
t1n
pb
pai * T(ti)
1 i .n
(b)
+
pl1
pln
T (t i )
1 - pi
C (t i )
1 - pi
tb
R(tli) =
T(t1n) =
(a)
tli
(b)
C(tli) =
pnb
pan
po1
T(tli) =
p1b
p2b +
+
…
+ pa2
ti
…
ta
+
…
t1
pa1
pi
…
•
•
•
•
•
•
(1 - pi ) * R (ti )
1 - pi R (ti )
F(tli).ar = f(pi, F(ti))
pai * C(ti)
C(t1n) =
1 i .n
pai * R(ti)
R(t1n) =
1 i .n
F(t1n).ar = f(pa1, F(t1), pa2, F(t2), …, pan, F(tn))
11/1/2013
Ten years of service research from a computer science perspective
36

37. Stochastic Workflow Reduction
(SWR) algorithm
Apply a set of reduction rules to a process until
only one atomic* task exists
Process w
For each rule applied, the process structure
changes
After several iterations only one task will
remain
N1
Sub-process w1
A
N2
B
C
D
The final task contains the QoS of the process
under analysis
Sub- process w2
N3
E
N4
F
qos(x1,..,xn)
Sub- process w3
G
11/1/2013
H
I
J
k
Ten years of service research from a computer science perspective
L
37

38. e.g. DNA Sequencing
11/1/2013
Ten years of service research from a computer science perspective
38

39. Semantic Web Services
11/1/2013
Semantic Web Services
Service Descriptions
Quality of Service
Process Complexity
Internet of Services
Service Networks
Ten years of service research from a computer science perspective
40

40. How Complex is a Process?
Product
Catalogue
Authoring at
Supplier
Data
Migration
System
Catalogue Authoring
External
Production Model
Processing
Product
Catalogue
Authoring at
Customer
Product
Catalogue
Authoring
updated on Jan 3rd 2007 (Jens Freund) -- interactions from dependent objects not included yet
Product Data
Management
Business Planning
Production
Model
Management
Opportunity /
Customer Quote
Processing at
Supplier
Product
Catalogue
Publishing
Service Request
Processing at
Provider
Activity
Management
Supply Chain Control
RFQ Processing
Catalogue Publishing
In-House
Requirement
Processing
RFQ
Processing
Purchasing
Contract
Processing
SAP Support
Request
Processing
Campaign
Management
RFQ
Processing
at Customer
Supply and
Demand
Matching
Source of
Supply
Determination
External
Procurement Trigger
and Response
SAP Service
Delivery
Processing
IT Change
Management
Service Request
Processing at
Requester
System
Administration
Service Request
Processing at
Provider
A
Customer
Quote
Processing
Customer
Requirement
Processing
IT Service and Application
Management
Software
Problem
Reporting
Service Request
Processing
Purchasing
Internal Request
Processing
Opportunity
Processing
Demand
Forecast
Processing
Sales Contract
Processing at
Supplier
Requisitioning
Service Delivery
Processing at
SAP
Customer Relationship Management
Lead
Processing
Groupware
Demand
Planning
Engineering
Change
Processing
Service
Contract
Processing
System
Administration
at Provider
A
A
Production
Trigger and
Response
Project Management
Purchase
Request
Processing
Project
Processing
Logistics
Execution
Control
Customer
Complaint
Processing
Purchase Order
Processing at
Customer
A
Sales Order
Processing
at
Supplier
Customer
Project Invoice
Preparation
Purchase Order
Processing
Sales Order
Processing
A
Data Flow
Verification
Service Order
Confirmation
Processing at
Customer
Service Order
Processing
Production and Site Logistics Execution
Production
A
A
A
Business
Configuration
A
Goods and
Service
Confirmation
at Supplier
Customer
Return
Processing
Goods and
Service
Acknowledgement
A
Outbound
Delivery
Processing
at Supplier
Inbound
Delivery
Processing
Outbound
Delivery
Processing
Inbound Delivery
Processing at
Customer
Service
Confirmation
Processing
Information
Lifecycle
Management
A
A
Document
Management
Supplier Invoicing
Customer Invoice
Processing at
Supplier
Supplier Invoice
Processing
Organisational
Management
Supplier Invoice
Processing at
Customer
Financial Accounting
A
Financial
Accounting Master
Data Management
CN Employer
Regulatory
Compliance
Tax
Processing
at Authority
Due Item Management
DE Employer
Regulatory
Compliance
Human Capital
Master Data
Management
Compensation
Management
FR Employer
Regulatory
Compliance
GB Employer
Regulatory
Compliance
Employee
Payroll
Administration
Due Item
Processing At
Business Partner
Expense and
Reimbursement
Management
Expense and
Reimbursement
Management
Due Item
Processing
Balance Of
Foreign Payment
Management
Processing of
Product Tax
Declaration at
Tax Authority
A
Processing of European
Community Sales List
Report at Tax Authority
A
Input and
Output
Management
A
Data
Migration
System
Processing of
Withholding
Tax
Declaration at
Tax Authority
Costing
Cash
Management
Resource Data
Management
Migration Data
Dispatching
Payment
Payroll
Accounting
Business
Document Flow
Processing
Migration Adapter
IT Employer
Regulatory
Compliance
US Employer
Regulatory
Compliance
Payroll
Processing at
Provider
Customer
Invoice
Processing
A
Personnel
Administration
A
Identity
Management
Customer Invoicing
Inventory
Processing
Business
Partner Data
Management
Human Capital Management
Time and
Labour
Management
Physical
Inventory
Processing
A
Data
Migration
System
A
Data
Migration
System
Site Logistics
Processing
Material
Inspection
Processing
Supplier Invoice
Verification
Exception Resolution
at Processor
Payment
Processing at
Business Partner
Payment
Processing
Installed Base
Data
Management
Site Logistics
Model
Management
Location Data
Management
Inspection
Master Data
Management
Logistics Area
and Storage
Management
Logistic Unit
Data
Management
A
Further Cash
Management
Relevant Component
Payment
Master Data
Management
Payroll Processing
Payment Order
Processing at
House Bank
Bank statement
creation at bank
Bill Of Exchange
Processing at
House Bank
LockBox File
creation at
provider
Settlement
Processing
at Clearing House
Price Master
Data
Management
Financial
Market Data
Management
Price Master Data
Management at
Customer
External Bank
Directory
Management
A
Deployment Unit
11/1/2013
Enterprise Service Interaction (cross Deplyoment Unit)
Direct Interaction (intra Deployment Unit)
Process components not assigned to a
deployment unit belong to foundation
Process Component
Ten years of service research from a computer science perspective
Process Component
at Business Partner
Third Party Process
Component
41

41. The Idea (2005)
Software Complexity
Process Complexity
Node Statement
(1)
(2)
(3)
while(x<100){
1
if (a[x] % 2 == 0) {
parity = 0;
}
2
else {
3
4
(4)
parity = 1;
(5)
}
5
(6)
switch(parity){
case 0:
(7)
println( “a[“ + i + “] is even”);
6
case 1:
(8)
println( “a[“ + i + “] is odd”); 9
7
8
default:
(9)
println( “Unexpected error”);
10
}
(10)
x++;
11
}
(11) p = true;
MCC=e - n + 2, where e and n are the
number of edges and nodes in the graph
Cardoso, J.; Mendling, J.; Neumann, G. and Reijers, H. A Discourse on Complexity of Process Models. Second International
Workshop on Business Process Intelligence, 2006.
11/1/2013
Ten years of service research from a computer science perspective
42

42. Views on Process Complexity
11/1/2013
Ten years of service research from a computer science perspective
43

43. Control-flow Complexity
Fan-out of the split
CFC ( P )
CFC XOR
i { XOR splits of P}
split
(i )
2n-1,where n is the
fan-out of the split
CFCOR
split
( j)
j {OR splits of P}
CFC AND
split
(k )
k { AND-splits of P}
1
Cardoso, J. Business Process Control-Flow Complexity: Metric, Evaluation, and Validation. In International Journal of Web Services
Research, Vol. 5 (2): 49-76, 2008.
11/1/2013
Ten years of service research from a computer science perspective
44

44. Understandability
Which one is more difficult to understand?
Start
Start
AND
A
XOR
XOR
XOR
OR
XOR
XOR
AND
XOR
A
B
C
I
K
L
Q
J
M
N
XOR
XOR
B
C
I
XOR
R
D
U
V
M
N
XOR
XOR
D
R
S
U
V
W
XOR
OR
P
O
XOR
AND
T
F
Q
W
XOR
OR
E
L
XOR
S
XOR
K
J
XOR
G
XOR
OR
H
E
F
OR
P
O
G
T
OR
XOR
XOR
H
AND
OR
XOR
XOR
End
11/1/2013
End
Ten years of service research from a computer science perspective
45

45. The Idea (2006)
“… the average connector degree is the
most convincing factor that relates to
model understandability, followed by a
model’s density”
The average connector degree refers to the number of
input and output arcs of a routing element
Mendling, J.; Reijers, H. and Cardoso, J. What Makes Process Models Understandable?. In The 5th International Conference on Business Process
Management (BPM 2007), 2007.
11/1/2013
Ten years of service research from a computer science perspective
46

46. Semantic Web Services
11/1/2013
Semantic Web Services
Service Descriptions
Quality of Service
Process Complexity
Internet of Services
Service Networks
Ten years of service research from a computer science perspective
47

47. The Problem
Service Engineering
11/1/2013
Ten years of service research from a computer science perspective
48

48. The Idea (2008)
Mental model
A Service
Model
Cardoso, J. The Internet of Services. In Proceedings of the 4th International
Conference on Software and Data Technologies , 2009
11/1/2013
A model is an abstraction
A model only focus on certain aspects
A model is created to describe a phenomena
Ten years of service research from a computer science perspective
49

49. The Idea (2008)
Definition
Requirements
Implementation Preparation Market Market Lunch
Design
Method =Technique and
Process
A Method
produces
models
Service
Workflow
Data
People
Rules
Scope Model
{contextual}
TXT, VISIO, PPT
description
of services
TXT, VISIO, PPT
description
of the workflow
TXT, VISIO, PPT
description
of data assets
TXT, VISIO, PPT
description
of organizational
units
TXT, VISIO, PPT
Goals and strategy
Business Model
{conceptual}
Formal definition
of functional/
non-functional
requirements
Formal definition
of functional/
non-functional,
BPMN
Interrelations
between
semantic
data assets
Organizational
chart
Business plan
(rules and
constraints)
Logical Model
{system}
A specific
construct
supporting a
method
(semantic) Interface,
message,
format,
data, etc
BPMN+
Semantic
data model
Interaction between
people and
service/processes
Business rule
model
Technical Model
{physical}
SAWSDL, WSDL,
SOAP, WS-Policy,
XML Schema,
XML, WSMO, etc
WS-Policy,
WS-CDL, WS-CI,
BPEL
OWL, RDFS,
XML Schema,
XML
GUI between
people and
services/processes.
Security model
WS-policy
RuleML, SWRL
Runtime
{operational}
WP7/WP10
WP7/WP10
WP7/WP10
WP7/WP10
WP7/WP10
A sequence of
actions
leading to
some result
Underlying concepts (paradigm)
E.g. service-oriented development
11/1/2013
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50

50. ISE Workbench
Executive
Manager
Business Analyst
Process Architect
Cardoso, J.; Winkler, M.; Voigt, K. and Berthold, H. IoS-Based Services, Platform Services, SLA and
Models for the Internet of Services. In Software and Data Technologies, Springer. 2009.
11/1/2013
Ten years of service research from a computer science perspective
51

51. Semantic Web Services
11/1/2013
Semantic Web Services
Service Descriptions
Quality of Service
Process Complexity
Internet of Services
Service Networks
Ten years of service research from a computer science perspective
52

52. …energy grids, water systems, wireless mobile networks...
The importance of networks
World Wide Web
Linked Data
Financial/Political Networks
Railway Network
11/1/2013
Ten years of service research from a computer science perspective
Social Networks
Food chain Networks
53

53. Service descriptions
•
Customers
• Avis Scandinavia
•
Supliers
• Oracle 11g or IBM DB2 database support
services.
•
Competitors
• SalesForce.com Sales Cloud, Microsoft OnDemand Dynamics CRM, and Oracle CRM
OnDemand
•
Complementors
• Sage ERP and Sugar ERP Business Suite are
complementors of SugarCRM
[CPL+12] Cardoso, J.; Pedrinaci, C.; Leidig, T.; Rupino, P. and Leenheer, P. D Open semantic service networks. In The International
Symposium on Services Science (ISSS 2012), pages 1-15, Leipzig, Germany, 2012.
11/1/2013
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54

54. The relationship problem
•
Given two services
– Does a relationship exists between
them?
– What is the support for the
relationship?
– What is the type of the relationship
[Car13]?
– What is the direction of the
relationship?
– What is the strength of the
relationship?
[Car13] Cardoso, J. Modeling Service Relationships for Service Networks. In 4th International Conference on Exploring Service Science
(IESS 1.3), pages 114-128, Springer, LNBIP, Porto, Portugal, 2013.
11/1/2013
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55

55. The relationship problem
11/1/2013
Ten years of service research from a computer science perspective
56

56. The centrality problem
•
Given a node and its neighbors
–
•
(Traditional) degree centrality
– A= 6
•
B
Popularity, power, collaboration
G
How to calculate Service centrality?





+ aG+aF
- bB - bC
+ cE
+ dD
C
A
F
D
E
Customers
Supliers
Competitors
Complementors
Ten years of service research from a computer science perspective
57
Can it be proved?
01-11-2013

57. Structural hole (Burt)
• Hypothesis
– People near holes in a social structure
are at higher risk of having
innovative ideas
• Level
– Individual
• What are the implications for
services?
• Leads to
– Power, influence, money, advanceme
nt, access, advantage
Competitive advantage is a matter of access to
structural holes in relation to market
transactions [Bur09]
– Discover new markets
– Evaluate the innovative potential
of organizations
[Bur09] Burt, Ronald S, Structural Holes: The Social Structure of Competition, Harvard University Press. 2009.
11/1/2013
Ten years of service research from a computer science perspective
58

58. The Idea (2012)
Service System & Relationships
The first steps …
Open Semantic Service
Relationship (OSSR)
•
•
•
•
Service description
Relationship description
Follows Linked Data principles
Means for publishing and interlinking
distributed services
[CPL+13] Cardoso, J.; Pedrinaci, C. and Leenheer, P. D Open Semantic Service Networks: Modeling and Analysis. In 4th International Conference
on Exploring Service Science (IESS 1.3), pages 141-154, Springer, LNBIP, Porto, Portugal, 2013.
01-11-2013
Ten years of service research from a computer science perspective
59

59. Thank You
for Listening