Smart city can be considered as a process-intensive environment that needs to be as flexible as possible to support a continuously evolving scenario. In this paper we present an approach to support flexibility of Business Processes regulating the behavior of ICT systems deployed within a smart city. The approach permits to deal with large collections of process variants thanks to the integration of Business Process notations and Feature Model descriptions. The approach is applied to a smart mobility scenario with a specific focus on bike sharing systems.

1. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Modelling Process Intensive Scenarios
for the Smart City
R. Cognini, F. Corradini, A. Polini, B. Re
University of Camerino
IFIP EGOV 2014
Trinity College, Dublin, Ireland
September, 3rd 2014
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

2. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Table of Contents
1 Motivations
2 A Smart City Scenario: The Bike Sharing System
3 bpFM - A Modeling Approach for BP variability
4 Conclusions and Future Work
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

3. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The Smart City
The Smart city vision foster the integration of complex
infrastructures and systems to better organize resource usage and
make the city more citizen centric
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

4. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The Smart Cities
Cities are dierent:
climate
terrain morphology
dimensions
inhabitants
. . .
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

5. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The Smart Cities
Cities are dierent:
climate
terrain morphology
dimensions
inhabitants
. . .
Therefore:
Smart cities will be dierent even if they will have to face
similar issues.
Dierences and similarities will be re
ected in the installed
systems and correspondingly in the supported business
processes that permit to organize and use the city
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

6. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Organizing BP for the Smart City
Our objective was to investigate on tools and languages permitting
to exploit commonalities still having the possibilities to derive
dierent version of the same system dipendently from the needs of
a speci

7. c smart city
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

8. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Organizing BP for the Smart City
Our objective was to investigate on tools and languages permitting
to exploit commonalities still having the possibilities to derive
dierent version of the same system dipendently from the needs of
a speci

9. c smart city
Two main ingredients:
Business Process Modeling
Software Product Line and Feature Modeling
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

10. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
BP modeling
A BP is the result of re
ection and synthesis on dierent aspects
of an organization, and in order to better set up its activities.
Particularly relevant for us are the functional, behavioral, and
information views.
BPMN2 (OMG standard) is currently the most used notation to
model BP. A simpli

11. ed view:
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

12. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Software Product Line and Feature Modeling
Software Product Lines (SPL)
refer to methods, tools and
techniques for creating a collection
of similar software systems
Feature Model (FM) is a modeling
approach emerged in the context of
SPL in order to support the
development of a variety of products
from a common platform
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

13. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The Bike Sharing System
The Bike Sharing System (BSS) is a bike rental solution that
enable citizens and tourists to move within a city using a bike. The
users of a BSS tipically pick up a bike from one of the bike station
(docking station) distributed in the city, and she can return it in
any other bike station
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

14. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The Bike Sharing System
The management and usage of the BSS subsumes the possibility of
activating many dierent BPs. Service subscription, bike
usage/travel, bike redistribution, credit acquisition, . . .
The Bike Usage/Travel Business Process refers to the BP family
permitting to a user (citizen or tourist) to register and access a
BSS to pick up a bike from a bike station, to use it to go around,
and

15. nally to return the bike to the same or a dierent bike station
(for instance including or not activities to apply rewarding policies)
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

16. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
The bpFM approach to variability modeling
The approach we propose mixes the characteristics and objectives of the two
dierent modeling context we introduced before.
To model BPs variability an extended version of FM has been introduced,
named business process Feature Model (bpFM), in which the features represent
the activities characterizing a process (functional view). Among the activities
relations are de

17. ned similarly to what is done in FODA.
A set of mapping rules from bpFM to BPMN 2.0 fragments has been de

18. ned
Successively according to a speci

19. c feature selection (con

20. guration) a detailed
BP skeleton can be automatically derived
It is also possible to add information concerning the input and output data
object related to an activity (information view)
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

21. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
bpFM Constrains
Elements in the bpFM notation permits to specify relation among
activities and if an activity has to be executed or not by a BP
enactment
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

22. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Mapping to BPMN
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

23. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Mapping to BPMN
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

24. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Mapping to BPMN
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

25. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Bike Travel of the BSS: The bpFM model
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

26. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Bike Travel of the BSS: Mapping Example
The selection of an activity (feature) results in the generation of
the correspondingly BP fragment
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

27. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Bike Travel of the BSS: The BP skeleton
The mapping rules permits to derive a variant skeleton including all
the selected activities given the con

28. guration, as well as the
de

29. nition of some behavioral constraints. The inclusion of data
ow relations further constraint the behavioral relations in the BP
skeleton
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

30. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Bike Travel of the BSS: A BP Variant
The BP variant is

31. nally obtained including all the behavioral
constraints
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

32. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
Conclusions and future work
Variability needs to be more and more taken into account also in order to
reduce costs. We presented an approach to model variability of BP
permitting to include in a single model many dierent variants of the
same BP. The approach permits to the modeler to focus on dierent
views (functional, behavioral, . . . ) at dierent times
Adopting the approach it is possible to reduce the complexity of
managing many dierent variants of a BP and to share experiences
between dierent smart city initiatives. The initial experiments we
conducted provided encouraging results.
There are many items in the future work list. Among the others:
continue experiments and validation

33. nalize the supporting tool chain
study the possible extension of the approach to consider
multi-organizational BPs
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

34. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
EU

35. nanced project
Model-Based Social Learning for Public Admin. (Learn PAd)
http://www.learnpad.eu
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City

36. Motivations
A Smart City Scenario: The Bike Sharing System
bpFM - A Modeling Approach for BP variability
Conclusions and Future Work
EU

37. nanced project
Model-Based Social Learning for Public Admin. (Learn PAd)
http://www.learnpad.eu
Thank you!
R. Cognini, F. Corradini, A. Polini, B. Re Modelling Process Intensive Scenario for the Smart City