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Commonly, the challenge of finding an appropriate level of abstraction is faced
with elimination and aggregation [14] [15]. A technique considering the semantic
relation between activities is presented in [16]. The meronymy-based aggregation
uses business process domain ontologies for abstraction. To enable aggregation, proc-
ess model activities are matched to an ontology. The technique offer transparency and
traceability in determining a particular abstraction level. However, preconditions of
this aggregation are a predefined ontology and the use of domain specific labels.
[1] proposes a scenario-based modeling paradigm which considers a process model
as a set of scenarios. While [1] considers all process views and divide them into proc-
ess fragments, we consider each process view of each process participant.
7 Conclusion
As so far the procedure of process models extraction from process information elic-
ited from process participants was handled like a black box, our main research interest
of this work was to find out how to translate various process elements captured in To-
do lists of individuals into a process model in a structured and traceable way. We
proposed the Business Process Model Extraction (BPME) method that supports a
transparent way of transforming process information in natural language into formal
process models. We discussed the potential of the qualitative content analysis in deal-
ing with differing levels of abstraction, heterogeneous labeling and the identification
of essential process elements. We presented guidelines for using the qualitative con-
tent analysis as a designer's tool to extract process information from To-do lists of
process participants in a structured, documented and traceable way. In order to sup-
port transparency and traceability up to the final process model, we presented guide-
lines to transform results of the content analysis into view process logs and discussed
two opportunities that lead to an entire process model by mining: the aggregation and
the merging of process views. In the case study we showed that the BPME method
could be successfully performed. The main challenges faced were the determination
of artificial time stamps in the process view logs that were crucial for process mining
and the elaboration of the possible process paths based on the decision paths in each
process view. The use of the BPME method offered the following outputs: (a) a
documented and traceable procedure of transforming To-do lists into the process
model, (b) illustrative personalized process view models, and (c) an illustrative proc-
ess model reflecting the To-do's of the process participants. In future work we will
extend our work on process view mining. Furthermore, we will offer more details
about the challenges of the elicitation step of the BPME method, and the validation of
the resulting models that should support our approach.
References
1.
Fahland, D., Weidlich, M.: Scenario-based process modeling with Greta. In: La Rosa, M.
(ed.) Proceedings of BPM Demonstration Track. CEUR-WS.org, Hoboken, vol. 615
(2010)
2.
Hammori, M., Herbst, J., Kleiner, N.: Interactive workflow mining - requirements, con-
cepts and implementation. Data & Knowledge Engineering 56, 41-63 (2006)
