Soundness Verification

Ensuring that the resulting business process model is sound is an important aspect of the quality of conceptual process models. Since a plethora of work on soundness verification exists in literature (see e.g. [vdA97, vdA00, DR01, vdAvH02, Mar03]), we aimed at reusing these techniques and incorporating them into our modeling framework. In order to do that, a Parser/Serializer component which translates the BPO process descriptions to plain pi-calculus syntax was necessary, along with the integration of a pi-calculus reasoning engine (see Fig. 6.1). The soundness verifica-tion algorithm used for checking process models is given in [PW06].

6.5 Implementation

In this section we discuss the implementation of a modeling tool, Semantic Mae-stro4BPMN⁸, based on the modeling technique presented above. Semantic Mae-stro4BPMN is an extension to the SAP Research Maestro modeling tool (cf. Section 5.4 for further technical details). We will now discuss the functionalities provided by the tool following the process modeling sub-activities depicted in Fig. 3.8.

Semantic Maestro4BPMN provides a modeling view with a simplified modeling notation for the manager modeling role (cf. Fig. 6.6). This notation is based on the

8Note that BPMN notation was selected for illustrative purposes due to its increasing popularity.

The modeling technique is independent from the concrete modeling notation

6.5 Implementation 115

most commonly used subset of the BPMN notation, defined through the analysis of over 100 process models from industry and academia in [MR08].

Figure 6.6: Most commonly used subset of BPMN constructs. Source: [MR08]

Using this notation, a business manager can design scenarios such as the one shown in Fig. 6.7. In the next step, she can annotate the scenario using the ontol-ogy instances from the ontolontol-ogy browser (lower right in Fig. 6.7). The annotations are visualized as circles in the modeling pane. For detailing each of the high-level scenario steps (subprocesses), the user can ask for recommendations (cf. Get Process Recommendation option for the Provide Service scenario step). Based on scenario an-notations, the process artifact repository is queried for matching modeling artifacts.

A list of matching results is shown in the query container on the left side of Fig.

6.7. The user can then drag-and-drop a query result to the scenario step in order to attach its detailed definition.

If a user wants to see the detailed subprocess definition that was attached, she can select the View Process Definition option for the desired scenario step (cf. Fig.

6.8).

Since the detailed process definition contains a richer set of modeling constructs, a new modeling view for the business analyst role is opened (see Fig. 6.9). The new view includes the additional constructs which allow for editing the target process model, while maintaining the linkage between two process modeling levels.

Finally, in the query view shown in Fig. 6.10, we show a ranked list of processes obtained as a result of the query built using the query designer. The user can browse the matching models from the process repository in order to reuse them in her de-sign.

Figure 6.7: Scenario modeling and process recommendation

Figure 6.8: View Process Definition option

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Figure 6.9: Business analyst view

6.6 Related Work

In [OSS94, LNO⁺89], the authors present INCOME approach for conceptual mod-eling of information systems. The approach uses Petri Nets [Pet62] as a uniform specification framework for all design-relevant static and dynamic system aspects.

It includes a prototyping environment which allows for validation early in the sys-tem design process. When positioned in the context of this thesis, INCOME ap-proach is placed between process levels 4 and 5 in Fig. 2.2, i.e. between the roles of business analyst and process architect. It covers mainly the functional, resource and behavioral perspective of processes, shown in Fig. 3.2. Compared to the IN-COME approach, our SBP modeling framework abstracts from system-level aspects and aims at providing modeling languages, methods and tools used earlier in the system design process.

The approach in [AS06] presents matchmaking of Web services based on π-calculus and description logics. The ontology is used for modeling input/output data exchanged between service operations. In our case, we capture broader and more high-level business knowledge in the ontology. Furthermore, with respect to the behavioral process perspective, we are mainly interested in the soundness ver-ification of process models. For this reason we needed to combine the pi-calculus with the ECA approach in order to be able to represent the semantics of all work-flow patterns. In contrast, the work in [AS06] does not consider the representation of complex flow structures but rather focuses on service matchmaking and substitu-tion mechanisms. In addisubstitu-tion, the authors follow the DL knowledge representasubstitu-tion

Figure 6.10: Process query view

paradigm (see Section 2.3.2) which is less suitable for querying large instance data sets (process descriptions) when compared to the LP paradigm used in our work.

Within the SUPER project, a Business Process Modeling Ontology (BPMO) is proposed for semantic representation of business processes. In the SBPM approach (see Section 2.4), the BPMO is supposed to model processes from the business per-spective while ontologized BPEL [AAA⁺07] does so from the technical perspective.

Since the main objective of SBPM approach is the automated mediation between the two perspectives, BPMO resulted in being a mere lightweight version of BPEL in order to enable the mapping between the two perspectives. Thus, it can be seen as rather an execution-level specification language than a business specification lan-guage. It fails to capture broad contextual business knowledge related to business processes. Furthermore, the BPMO does not allow for modeling behavioral seman-tics of processes which prevents the possibility of performing process soundness verification.

Related to this, the work in [Web09] presents an approach for supporting pro-cess modelers in designing execution-level business propro-cess models, using semantic

6.7 Conclusion 119

technologies. The approach is based on describing the semantics of process activi-ties in terms of their change semantics⁹, i.e. annotating their pre- and postconditions.

Such annotated process models are used to design two modeling techniques for the modeling support: task composition and verification. The verification of annotated process models here refers to checks such as i) are there any two activities executing in parallel that have conflicting effects, ii) are preconditions for all activities always satisfied and iii) can every activity in the process be reached [Web09]. This work thus focuses on providing modeling techniques for the execution-level business process models (in between levels 4 and 5 in Fig. 2.2) and can be seen as complementary to our work.

The significance of querying business processes has been acknowledged by BPMI¹⁰ who launched a Business Process Query Language (BPQL) initiative [BPM].

However, no standard specification has been published yet.

In [BEKM06], the authors present a query language for querying business pro-cesses, BP-QL. The query language is designed based on the BPEL standard and thus focuses on querying executable processes. In addition, the language is graph-based and therefore only supports querying the process structure.

6.7 Conclusion

This chapter presents a modeling technique and tool for modeling and querying of business processes on a semantic level. After identifying a list of requirements, we start with discussing the modeling language to be used for semantic business pro-cess modeling. The syntax and semantics of this language is provided by means of the Business Process Ontology and for illustrating purposes we take the widely adopted BPMN as the modeling notation. Further, we present a modeling method which profits from a semantically rich process representation to provide the ele-ments which introduce the benefits of its usage. Finally, we discuss the prototypi-cal implementation of the modeling technique as an extension to the SAP Research modeling tool Maestro and contrast our contributions to the related efforts.

9This notion is well-known in the actions and change community within the field of artificial intelligence

10Business Process Management Initiative, http://www.bpmi.org/

Part III

Finale

Chapter 7 Evaluation

Evaluation of the quality of conceptual models, such as the ones presented in this thesis represents a challenge. This is due to the fact that there is no quality frame-work which is commonly accepted in practice, despite their proliferation in research literature, see e.g. [LSS94, BRvU00, VCM⁺07]. Moody [Moo05] identifies several is-sues in the existing research on quality frameworks which led to this state: lack of testing and acceptance in practice, different levels of generality, lack of agreement on terminology, lack of evaluation procedures and improvement guidelines, etc. This is why conceptual modeling is still considered an art rather than an engineering discipline.

On the other hand, ensuring the quality of conceptual models is of high impor-tance since the cost of errors increases exponentially over the system development lifecycle [Moo05]. Also, empirical studies show that more than half of the errors occurring during the system development are errors where requirements specifica-tions do not match the actual user requirements [ER03].

In order to evaluate the quality of the proposed SBP modeling framework, we take a multi-viewpoint approach and perform the evaluation based on four different aspects. First, in Section 7.1 we compare the modeling framework to established and influential modeling approaches in the field based on several criteria. Second, in Section 7.2 we investigate the modeling content of one of the largest software providers to understand its conceptual model and map it to the process-oriented ontology framework for evaluating its representational completeness. We also test the performance and scalability of the process querying method using a large data set of business processes. In Section 7.3, we evaluate the applicability of the policy and rule modeling approach using two real-life business scenarios. Section 7.4 gives an overview of the application and impact of research results presented here within SAP projects. Finally, Section 7.5 concludes the chapter.

7.1 Comparison with Influential Modeling Approaches

Process-oriented modeling approaches in computer science received growing at-tention from the beginning of the 1990s onwards, strongly advocating to give up the purely functional structuring of enterprises in favor of a process-oriented view [HC93]. Some approaches to business process modeling using information systems even date back to the 1980s [Sch88]. Sections 3.2.2 and 3.2.3 motivated different viewpoints that business process modeling is concerned with. In this section we

build upon these descriptions and define criteria for the comparison of common modeling approaches, both from academia and from industry.