=Paper=
{{Paper
|id=Vol-1815/paper29
|storemode=property
|title=Work ow Modelling Assistance by Means of Process-oriented Case-based Reasoning
|pdfUrl=https://ceur-ws.org/Vol-1815/paper29.pdf
|volume=Vol-1815
|authors=Gilbert Müller
|dblpUrl=https://dblp.org/rec/conf/iccbr/Muller16
}}
==Work ow Modelling Assistance by Means of Process-oriented Case-based Reasoning==
https://ceur-ws.org/Vol-1815/paper29.pdf
272
Workflow Modelling Assistance by Means of
Process-oriented Case-based Reasoning
Gilbert Müller
Business Information Systems II
University of Trier
54286 Trier, Germany
muellerg@uni-trier.de,
http://www.wi2.uni-trier.de
In recent years, workflows have become an important paradigm to represent pro-
cesses in many application areas. Traditionally known from the field of business
processes, workflows are “the automation of a business process, in whole or part,
during which documents, information or tasks are passed from one participant
to another for action, according to a set of procedural rules” [25]. Today, their
application has extended towards various other domains such as healthcare [7],
or the analysis of large data sets employing so called scientific workflows [24].
Moreover, they are considered as a novel programming paradigm [14] and can
also be used to represent simple processes like cooking instructions [22].
In all these domains, the creation of workflows (also refered to as workflow
modelling) is a complex and time consuming task. Consequently, in order to ease
their creation, reuse becomes an important key to the successful application of
the workflow paradigm. Workflow reuse is usually supported by search methods
capturing the current needs and requirements in a query or a partial workflow.
Based on this, a previously modelled workflow is identified which at best matches
the current scenario. Thus, the workflow does not have to be modelled from
scratch. Various approaches already exist for such search-based workflow reuse
(e.g., [5,8,2,3]).
However, workflow adaptations are required more often due to an increased
individuality demand of workflows, i.e., workflows need to be tailored to the
particular needs or scenario more frequently. Manual workflow adaptation may
become an elaborate task. Thus, methods supporting workflow adaptations are of
high relevance. In this regard, Process-oriented Case-based Reasoning (POCBR)
[13] can be a means to support the creation and adaptation of processes that
are, e.g., represented as workflows. Although, POCBR is of high relevance little
research exists so far, in particular addressing workflow adaptation (e.g., [12]).
The presented approach addresses workflow modelling assistance by means
of POCBR, in particular focussing on the adaptation of workflows. Adapta-
tion requires knowledge, e.g., in the form of adaptation rules. The modelling of
Copyright c 2016 for this paper by its authors. Copying permitted for private and
academic purposes. In Proceedings of the ICCBR 2016 Workshops. Atlanta, Georgia,
United States of America
273
such domain specific adaptation knowledge, however, is expensive and requires
a deep understanding of the adaptation methods. This results in an acquisition
bottleneck for adaptation knowledge [9]. Thus, the approach includes automated
learning of adaptation knowledge to prevent limited adaptation capabilities.
1 Approach
The overall approach for workflow modelling support by means of Process-
Oriented Case-based Reasoning is illustrated in Figure 1. In order to determine
the requirements and needs on the workflow to be modelled, the query lan-
guage POQL [19] basically captures workflow elements or subworkflows that are
desired or undesired. Thus, the best matching workflow from a case base (or
workflow repository respectively) of previously modelled workflows can be iden-
tified. Next, workflow adaptations are executed in order to increase the fulfilment
of the adapted workflow w.r.t. the POQL query. Hence, the retrieved workflow
W is transformed into an adapted workflow Wn by chaining various adaptation
s1 s2 sn
steps W → W1 → ... → Wn . This process can in principle be considered a
search process towards an optimal solution w.r.t. the query.
retrieval adaptation specialization
?
POQL Query
workflow from adapted generalized workflow adapted workflow
generalized casebase
generalize learn
case base adaptation
knowledge
casebase generalized workflow adaptation
case base streams operators
Fig. 1. Overall workflow adaptation process
These adaptation steps are performed by different adaptation approaches,
which are integrated in a single process such that they can be executed in alliance
in order to improve adaptation capabilities [16]. More precisely, compositional
adaptation [15] primarily replaces meaningful subcomponents of a workflow,
called workflow streams, by more appropriate subcomponents of other workflows.
Subsequently, adaptation operators [18], which are learned automatically from
the case base, enable to remove, insert, or replace smaller workflow fragments.
This adaptation process is further enhanced by generalization of workflows and
adaptation knowledge [17]. Both consist of generalized workflow elements that
are placeholders representing a set of possible elements. The adapted workflow
containing such elements, is finally specialized according to the given query, i.e.,
suitable workflow elements are chosen.
Consequently, adaptation is executed based on the best maching workflow
from the repository. However, Smyth and Keane [23] already stated, that it
274
is important to reflect the adaptability during retrieval. Otherwise, retrieval
may provide a workflow that cannot be at best adapted according to the query.
Thus, the optimal workflow solution w.r.t. the query cannot always be ensured.
Hence, there is a demand for methods enabling the assessment of adaptability of
workflows, for example, by executing various example adaptations [6]. The main
assumption is that workflows that are very adaptable in many scenarios are also
highly adaptable in other scenarios. The computed adaptability value of the
workflow can then be considered during retrieval. Another threat for retrieval
and adaptation of workflows are insufficiently defined workflow models in the
repository. Such a lack of information can result in inappropriate workflows
selected during retrieval or incompletely generated adaptation knowledge. Both
hamper the presented workflow modelling assistance. To prevent this, workflow
completion [20] aims at deriving the missing information automatically prior to
retrieval and adaptation.
The modelling assistance has been implemented and evaluated using the
CAKE (Collaborative Agent-based Knowledge Engine) framework 1 developed
at the University of Trier [4]. The CookingCAKE2 prototype [16] demonstrates
the presented approach in the cooking domain, where workflows represent cook-
ing instructions consisting of preparation steps and involved ingredients.
2 Future Work
Future work comprises approaches for supporting the manual adaptation of
workflows by means of the developed POCBR adaptation methods. A draw-
back of applying adaptation methods automatically, is that the adaptation goal
must mostly be known previously. Consequently, this can lead to a non-optimal
or undesired solution. Hence, user interaction [1] is a promising approach to
overcome this drawback. Interactive adaptation could support the search of a
suitable query and hence the desired solutions. The idea for supporting workflow
adaptation is that the user is involved directly during adaptation by manipu-
lating the workflow manually. Based on the users’ workflow manipulations, the
query can be refined automatically. Subsequently, suggestions are made about a
possible automatic workflow adaptation. This suggested adaptation can be ac-
cepted or rejected by the user. This process, helps to refine the query stepwise
and overcomes the drawback of an extensive search for the desired solution.
Finally, the developed methods will be analysed by an extensive summa-
tive evaluation. While the adaptation approaches have already been assessed
seperately, an overall evaluation is planned to enable a comparison between the
presented approaches. Main factors affecting the utility of workflow adaptations
are the increased fulfilment of the workflow after adaptation w.r.t. the query
as well as the quality of the adapted workflow. Thereto, quality metrics will be
based on various quality frameworks [11,21,10].
1
cakeflow.wi2.uni-trier.de
2
http://cookingcake.wi2.uni-trier.de
275
An analytical evaluation will provide information about several computable
quality metrics such as the complexity of the workflow, the throughput time of
the workflow as well as the fulfillment of the query. Further, an experimental
evaluation will be used to capture a more user-oriented view on the workflow
quality and further aims at investigating the utility of adapted workflows. The
basic approach is, that the workflow quality will be assessed by a blind experi-
ment ignoring the query in which the users rate the adapted workflow and the
retrieved workflow, not knowing which of these workflows have been adapted.
Then, they rate several items on a likert scale to acquire users perceptions on the
workflow models quality. Thus, the quality of the retrieved and adapted work-
flows can be compared and conclusions on the impact of the workflow adaptation
methods on the workflow quality can be drawn. Moreover, the utility of workflow
adaptation methods is investigated. Since utility depends on the current goals
[21], workflow utility can only be assessed knowing the query. Then, users rate
whether they prefer the adapted or the retrieved workflow.
All workflow adaptation methods will be investigated in a joint as well as in
separate applications. Thus, a comparison of the different adaptation methods
can be achieved and conclusions on the overall adaptation process can be made.
References
1. Aha, D.W., Muñoz-Avila, H.: Introduction: Interactive case-based reasoning. Appl.
Intell. 14(1) (2001)
2. Awad, A.: BPMN-Q: A language to query business processes. In: Reichert, M.,
Strecker, S., Turowski, K. (eds.) Enterprise Modelling and Information Systems
Architectures - Concepts and Applications , Proceedings of EMISA’07, St. Goar,
Germany, 2007. LNI, vol. P-119. GI (2007)
3. Becker, M., Laue, R.: A comparative survey of business process similarity measures.
Computers in Industry 63(2) (2012)
4. Bergmann, R., Gessinger, S., Görg, S., Müller, G.: The collaborative agile knowl-
edge engine CAKE. In: Goggins, S.P., Jahnke, I., McDonald, D.W., Bjørn, P. (eds.)
Proceedings of GROUP’14, Sanibel Island, FL, USA, 2014. ACM (2014)
5. Bergmann, R., Gil, Y.: Similarity assessment and efficient retrieval of semantic
workflows. Inf. Syst. 40 (2014)
6. Bergmann, R., Müller, G., Zeyen, C., Manderscheid, J.: Retrieving adaptable cases
in process-oriented case-based reasoning. In: Markov, Z., Russell, I. (eds.) Proceed-
ings of FLAIRS 2016, Key Largo, Florida, 2016. AAAI Press (2016)
7. Dadam, P., Reichert, M., Kuhn, K.: Clinical Workflows - The Killer Application
for Process-oriented Information Systems? Springer, London (2000)
8. Dijkman, R.M., Dumas, M., van Dongen, B.F., Käärik, R., Mendling, J.: Similarity
of business process models: Metrics and evaluation. Inf. Syst. 36(2) (2011)
9. Hanney, K., Keane, M.T.: The adaptation knowledge bottleneck: How to ease it
by learning from cases. Springer Berlin Heidelberg (1997)
10. Jansen-Vullers, M., Loosschilder, M., Kleingeld, P., Reijers, H.: Performance mea-
sures to evaluate the impact of best practices. In: Proceedings of Workshops and
Doctoral Consortium of the 19th International Conference on Advanced Infor-
mation Systems Engineering (BPMDS workshop). vol. 1. Tapir Academic Press
Trondheim (2007)
276
11. Lindland, O.I., Sindre, G., Sølvberg, A.: Understanding quality in conceptual mod-
eling. IEEE Software 11(2) (1994)
12. Minor, M., Bergmann, R., Görg, S., Walter, K.: Towards case-based adaptation of
workflows. In: Bichindaritz, I., Montani, S. (eds.) Case-Based Reasoning. Research
and Development, ICCBR 2010, Alessandria, Italy, July 19-22, 2010. Proceedings.
LNCS, vol. 6176. Springer (2010)
13. Minor, M., Montani, S., Recio-Garcı́a, J.A.: Process-oriented case-based reasoning.
Inf. Syst. 40 (2014)
14. Morrison, J.P.: Flow-Based programming: A new approach to application develop-
ment. CreateSpace, Paramount, CA (2010)
15. Müller, G., Bergmann, R.: Workflow streams: A means for compositional adap-
tation in process-oriented CBR. In: Lamontagne, L., Plaza, E. (eds.) Case-Based
Reasoning Research and Development, ICCBR 2014, Cork, Ireland, 2014. Proceed-
ings. LNCS, vol. 8765. Springer (2014)
16. Müller, G., Bergmann, R.: CookingCAKE: A framework for the adaptation of
cooking recipes represented as workflows. In: Kendall-Morwick, J. (ed.) Workshop
Proceedings of ICCBR 2015, Frankfurt, Germany, 2015. CEUR Workshop Pro-
ceedings, vol. 1520. CEUR-WS.org (2015)
17. Müller, G., Bergmann, R.: Generalization of workflows in process-oriented case-
based reasoning. In: Russell, I., Eberle, W. (eds.) Proceedings of FLAIRS 2015,
Hollywood, Florida. 2015. AAAI Press (2015)
18. Müller, G., Bergmann, R.: Learning and applying adaptation operators in process-
oriented case-based reasoning. In: Hüllermeier, E., Minor, M. (eds.) Case-Based
Reasoning Research and Development, ICCBR 2015, Frankfurt am Main, Germany,
2015, Proceedings. LNCS, vol. 9343. Springer (2015)
19. Müller, G., Bergmann, R.: POQL: A new query language for process-oriented case-
based reasoning. In: Bergmann, R., Görg, S., Müller, G. (eds.) Proceedings of
the LWA 2015 Workshops, Trier, Germany, October 7-9, 2015. CEUR Workshop
Proceedings, vol. 1458. CEUR-WS.org (2015)
20. Müller, G., Bergmann, R.: Case completion of workflows for process-oriented case-
based reasoning. In: Proceedings of ICCBR 2016. Atlanta (Georgia), USA (2016)
21. Rittgen, P.: Quality and perceived usefulness of process models. In: Shin, S.Y.,
Ossowski, S., Schumacher, M., Palakal, M.J., Hung, C. (eds.) Proceedings of the
ACM Symposium on Applied Computing (SAC), Sierre, Switzerland,, 2010. ACM
(2010)
22. Schumacher, P.: Workflow Extraction from Textual Process Descriptions. Ph.D.
thesis, Wolfgang Goethe University, Frankfurt/Main (2016)
23. Smyth, B., Keane, M.T.: Retrieving adaptable cases: The role of adaptation knowl-
edge in case retrieval. In: Wess, S., Althoff, K., Richter, M.M. (eds.) Topics in
Case-Based Reasoning, EWCBR-93, Kaiserslautern, Germany, 1993. LNCS, vol.
837. Springer (1993)
24. Taylor, I.J., Deelman, E., Gannon, D.B., Shields, M.: Workflows for e-science -
Scientific workflows for grids. Springer, London (2007)
25. Workflow Management Coalition: Workflow management coalition glossary & ter-
minology. http://www.wfmc.org/docs/TC-1011_term_glossary_v3.pdf (1999),
last access on 20-09-2016