=Paper=
{{Paper
|id=Vol-3113/paper8
|storemode=property
|title=Preserving Data Consistency in Process Choreographies by Design (short paper)
|pdfUrl=https://ceur-ws.org/Vol-3113/paper8.pdf
|volume=Vol-3113
|authors=Tom Lichtenstein
|dblpUrl=https://dblp.org/rec/conf/zeus/Lichtenstein22
}}
==Preserving Data Consistency in Process Choreographies by Design (short paper)==
https://ceur-ws.org/Vol-3113/paper8.pdf
Preserving Data Consistency in Process
Choreographies by Design
Tom Lichtenstein
Hasso Plattner Institute, University of Potsdam, Potsdam, Germany
Tom.Lichtenstein@hpi.de
Abstract. Data is essential for the execution of business processes. As
today’s organizations increasingly collaborate in process choreographies,
data relevant to process execution is typically shared among partici-
pants. To avoid conflicts in the execution of process choreographies, the
preservation of data consistency must be considered in the design of a
choreography. However, current choreography modeling languages provide
limited data modeling capabilities, thus potential conflicts arising from
data inconsistencies at runtime may remain undetected during design
time. Therefore, this paper motivates a framework allowing the design of
data consistency-aware process choreographies.
Keywords: Process Choreography · Data Consistency · Design Time
1 Introduction and Motivating Example
In the current age of information, business processes and their outcomes rely on
data and its manipulation during process execution [16]. As today’s organizations
increasingly collaborate in process choreographies [18], data relevant to business
process execution is typically shared across choreography participants. To ensure
the correct execution of the individual business processes involved in a process
choreography, data consistency, i.e., a uniform view of data shared across multiple
nodes [15], is a desirable property to be maintained among participants [12]. As
the participants can only exchange data in the form of messages, maintaining
data consistency is particularly challenging in process choreographies. Local
changes to data shared with other participants can result in inconsistent views
of the data, which may lead to conflicts such as unexpected interactions or data
constraint violations on the receiving end. Since any deviation from the agreed
interaction behavior can affect operations and incur costs, process choreographies
require careful coordination [18]. Therefore, interaction behavior arising from
data inconsistencies needs to be considered during process choreography design.
The consideration of data consistency during design time is particularly relevant
for process choreographies since in process orchestrations consistency can usually
be enforced via central database management systems.
To support the design of process choreographies, graphical modeling lan-
guages such as Business Process Model and Notation (BPMN) [1] can be used.
However, most contemporary choreography modeling languages provide only
J. Manner, D. Lübke, S. Haarmann, S. Kolb, N. Herzberg, O. Kopp (Eds.): 14th ZEUS
Workshop, ZEUS 2022, Bamberg, held virtually due to Covid-19 pandemic, Germany, 24–25
February 2022, published at http://ceur-ws.org
Copyright © 2022 for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0).
52 Tom Lichtenstein
limited data modeling capabilities. Therefore, potentially erroneous behavior
resulting from data inconsistencies may remain undetected during design time.
To illustrate the relevance of data management in choreography design, we con-
sider a simple online ticket reservation choreography depicted in Figure 1. The
choreography starts with a customer querying and selecting available seats for
an event. Then, depending on the price offer, the customer decides whether
to cancel the reservation or book the tickets. In the latter case, the ticket
store confirms the reservation. While the interaction behavior is locally en-
forceable [19], data inconsistencies may arise with concurrent executions. As-
suming that the ticket shop can sell only one ticket for each seat, if two cus-
tomers select overlapping seats and the reservation of the first customer is
confirmed, the second customer has an inconsistent view of the available seats.
Furthermore, since the confirmation of
the second reservation would lead to a
constraint violation on the part of the
ticket shop, compensation behavior is Customer
Query
Customer Customer Ticket Shop
Select Book Confirm
required to restore the consistency be- available seats tickets
seats booking
Ticket Shop Ticket Shop Ticket Shop Customer
tween the participants. Still, the need
for compensation and the compensa- Ticket Shop Customer
Offer Cancel
tion behavior itself are both not ev- price booking
ident from the given model. In the Customer Ticket Shop
following, related work in the area of
data consistency preservation is dis- Fig. 1. Ticket reservation choreography be-
cussed and a framework for designing tween a customer and an online ticket shop
consistency-aware process choreogra-
phies is motivated.
2 Related Work
Maintaining consistency in distributed environments is extensively studied in
literature [3,6,10]. In particular, the preservation of data consistency is addressed
by consensus protocols [11] which allow distributed nodes to agree on specific
data values required for further computation, thus providing a consistent view
of the data. The application of consensus protocols to process choreographies
is discussed by Weber et al. [17]. The authors propose the use of blockchain
technology [14] as an execution environment for process choreographies. To model
and execute blockchain-driven choreographies, Ladleif et al. [9] refine BPMN
2.0 choreography diagrams [1] with blockchain-specific extensions. However,
maintaining consensus in process choreographies may introduce synchronization
overhead as not every change needs to be propagated to all participants. Moreover,
in scenarios where inconsistencies rarely lead to conflicts, sustaining consensus
among all participants may limit concurrent behavior and thus affect throughput.
Incorporating data consistency management into the interaction design instead
allows the choreography to be flexibly tailored to the use case.
Preserving Data Consistency in Process Choreographies by Design 53
Despite the existence of approaches that enrich choreography models with
data management-specific information [5,13], the preservation of data consistency
in process choreographies with concurrent instances has received little attention
in research. Hahn et al. [5] introduce an approach that decouples the data flow
between participants from the message flow by introducing a middleware that
coordinates cross-partner data objects among corresponding participants. Yet, the
handling of concurrent accesses to data shared by multiple instances is not further
specified in their approach. Haarmann et al. [4] introduce a framework to analyze
the use of shared data in process models by defining data access semantics. While
the framework includes concepts for data consistency preservation, it does not
address data exchange between individual participants. Finally, Kopp et al. [8]
propose choreography spheres ensuring transactional behavior for all included
activities that may belong to different processes. Still, deciding on an adequate
scope of the spheres might prove challenging without data-related information,
as overly large transactions could create avoidable overhead.
3 Towards Data Consistency in Process Choreographies
Since the integration of existing data consistency-preserving concepts into the de-
sign of process choreographies poses various challenges as outlined in the previous
section, this paper proposes the concept of a framework supporting the collab-
orative design of data consistency-aware process choreographies based on the
BPMN modeling language. The framework is supposed to enable the detection of
potential data inconsistencies between participants at design time that may lead
to conflicts at runtime. To achieve this, the framework will include functionality
to specify and verify data consistency-related information in process choreography
diagrams. Thus, participants should be enabled to define data consistency con-
straints at the interaction level (i.e., in the public process) that must be followed
in the individual data management of each participant’s local behavior (i.e., in
the private process). The specifications will also allow participants to identify
activities or data objects that may be affected by inconsistent data and therefore
require careful attention in their design. In addition, data consistency criteria
are introduced to formally verify the preservation of consistency throughout the
choreography with regard to the specifications. The criteria should allow the
detection of interaction behaviors that potentially lead to conflicts considering
data inconsistencies that are not resolved in subsequent interactions. To design
the criteria, existing formal definitions of consistency models [15] and data-aware
choreographies [2,7] will be considered. Formal verification based on choreography
models may also require extending the BPMN modeling language to include
information about the individual management of the exchanged data. Eventually,
the framework can be used to automatically derive enhanced process designs
when potential conflicts are identified.
Based on this framework, a methodology will be developed to enable business
engineers to iteratively redesign interaction behaviors prone to inconsistencies.
The redesigned behavior is supposed to either ensure data consistency until
54 Tom Lichtenstein
the interactions affected by the data are completed or include appropriate com-
pensation behavior to restore consistency. To realize the proposed concept, the
following research questions need to be answered:
– Which information is required to reason about data consistency across multi-
ple interactions while also considering concurrent behavior?
– How can data consistency-related information be integrated into the design
of process choreographies?
– How can the behavior of process choreographies be enhanced to avoid conflicts
caused by data inconsistencies?
4 Conclusion
This position paper discusses the need for considering the preservation of data
consistency when designing process choreographies. Since current choreography
modeling languages provide limited support for data modeling, potential conflicts
due to data inconsistencies between participants may go undetected during
design time. By integrating data consistency-related information into the design
of process choreographies, corresponding conflicts can be detected and addressed
to ensure a more reliable interaction behavior.
References
1. Business process model and notation (BPMN), version 2.0 (2011), http://www.omg.
org/spec/BPMN/2.0
2. Corradini, F., Muzi, C., Re, B., Rossi, L., Tiezzi, F.: Animating multiple instances
in BPMN collaborations: From formal semantics to tool support. In: Weske, M.,
Montali, M., Weber, I., vom Brocke, J. (eds.) Business Process Management,
Lecture Notes in Computer Science, vol. 11080, pp. 83–101. Springer International
Publishing, Cham (2018). https://doi.org/10.1007/978-3-319-98648-7_6
3. Gilbert, S., Lynch, N.: Brewer’s conjecture and the feasibility of consistent, available,
partition-tolerant web services. ACM SIGACT News 33(2), 51–59 (2002). https:
//doi.org/10.1145/564585.564601
4. Haarmann, S., Weske, M.: Cross-case data objects in business processes: Semantics
and analysis. In: Fahland, D., Ghidini, C., Becker, J., Dumas, M. (eds.) Business
Process Management Forum, Lecture Notes in Business Information Processing,
vol. 392, pp. 3–17. Springer International Publishing, Cham (2020). https://doi.
org/10.1007/978-3-030-58638-6_1
5. Hahn, M., Breitenbücher, U., Kopp, O., Leymann, F.: Modeling and execution of
data-aware choreographies: an overview. Computer Science - Research and Devel-
opment 33(3-4), 329–340 (2018). https://doi.org/10.1007/s00450-017-0387-y
6. Herlihy, M.P., Wing, J.M.: Linearizability: a correctness condition for concurrent
objects. ACM Transactions on Programming Languages and Systems 12(3), 463–492
(1990). https://doi.org/10.1145/78969.78972
7. Knuplesch, D., Pryss, R., Reichert, M.: Data-aware interaction in distributed
and collaborative workflows: Modeling, semantics, correctness. In: Pu, C., Joshi,
J., Nepal, S. (eds.) Proceedings of the 8th IEEE International Conference on
Collaborative Computing: Networking, Applications and Worksharing. IEEE (2012).
https://doi.org/10.4108/icst.collaboratecom.2012.250443
Preserving Data Consistency in Process Choreographies by Design 55
8. Kopp, O., Wieland, M., Leymann, F.: Towards choreography transactions. In: Oliver
Kopp, Niels Lohmann (eds.) 1st Central-European Workshop on Services and their
Composition, ZEUS 2009, Stuttgart, Germany, March 2-3, 2009. Proceedings. CEUR
Workshop Proceedings, CEUR-WS.org (2009)
9. Ladleif, J., Weske, M., Weber, I.: Modeling and enforcing blockchain-based chore-
ographies. In: Hildebrandt, T., van Dongen, B.F., Röglinger, M., Mendling,
J. (eds.) Business Process Management, Lecture Notes in Computer Science,
vol. 11675, pp. 69–85. Springer International Publishing, Cham (2019). https:
//doi.org/10.1007/978-3-030-26619-6_7
10. Lamport, L.: Time, clocks, and the ordering of events in a distributed system.
Communications of the ACM 21(7), 558–565 (1978). https://doi.org/10.1145/
359545.359563
11. Lamport, L.: The part-time parliament. ACM Transactions on Computer Systems
16(2), 133–169 (1998). https://doi.org/10.1145/279227.279229
12. Liu, X.: Data consistency enforcement on business process transactions. In: Service-
Oriented Computing, pp. 394–399. Springer Berlin Heidelberg (2013). https://
doi.org/10.1007/978-3-642-37804-1_40
13. Meyer, A., Pufahl, L., Batoulis, K., Fahland, D., Weske, M.: Automating data
exchange in process choreographies. Information Systems 53, 296–329 (2015).
https://doi.org/10.1016/j.is.2015.03.008
14. Nakamoto, S.: Bitcoin: A peer-to-peer electronic cash system (2008)
15. Tanenbaum, A.S., van Steen, M.: Distributed Systems: Principles and Paradigms.
Pearson Education (2008)
16. Tsoury, A., Soffer, P., Reinhartz-Berger, I.: Data impact analysis in business
processes. Business & Information Systems Engineering 62(1), 41–60 (2020). https:
//doi.org/10.1007/s12599-019-00611-5
17. Weber, I., Xu, X., Riveret, R., Governatori, G., Ponomarev, A., Mendling, J.:
Untrusted business process monitoring and execution using blockchain. In: La Rosa,
M., Loos, P., Pastor, O. (eds.) Business Process Management, Lecture Notes in
Computer Science, vol. 9850, pp. 329–347. Springer International Publishing, Cham
(2016). https://doi.org/10.1007/978-3-319-45348-4_19
18. Weske, M.: Business Process Management. Springer Berlin Heidelberg, Berlin,
Heidelberg (2019). https://doi.org/10.1007/978-3-662-59432-2
19. Zaha, J., Dumas, M., Hofstede, A., Barros, A., Decker, G.: Service interaction
modeling: Bridging global and local views. In: 2006 10th IEEE International
Enterprise Distributed Object Computing Conference (EDOC’06). pp. 45–55. IEEE
(10/16/2006 - 10/16/2006). https://doi.org/10.1109/EDOC.2006.50