Reference models can be considered as special conceptual models that serve to be reused for the design of other conceptual models. Due to an ongoing need for high-quality reference models, reference model mining, i.e. the (semi-)automatic derivation of reference models from a set of existing process models, has recently gained the attention of researchers. The presented dissertation project addresses the concept of Situational Reference Model Mining, i.e. the idea that mined reference models, although based on the same input data, are intended for di erent use cases and thus have to meet di erent requirements. These requirements determine the reference model character and thus the technique that is best suited for mining it. The dissertation's major objective is to design, elaborate, and validate a method for Situational Reference Model Mining, which provides reference modelers with a clear guideline on how to use automated reference model mining techniques to their advantage.
Reference models can be considered as special conceptual models that serve to be
reused for the design of other conceptual models [
Leveraging the multiple bene ts of reference modeling in both research and practice depends on the widespread availability of high-quality reference models. Generally accepted and widely used reference models exist only for a few industries, such as the IT Infrastructure Library (ITIL) for IT service management or 1This section is based on previous work presented in [1{3] and has been adapted. the Supply Chain Operations Reference Model (SCOR) for supply chain management, eliciting an ongoing need for reference model construction methods.
Reference models may be constructed both deductively and inductively. Deductive methods or \top-down" approaches employ generally accepted theories and principles. Models are constructed on a theoretical base and gradually substantiated along the way. In contrast, inductive or \bottom-up" development of reference models makes use of real-world data such as existing process models or execution logs. It focuses on similarities and commonalities within the input data and abstracts from a model's individual features. As is it possible to automate the inductive derivation of a potential reference model from a collection of existing process models (Reference Model Mining), inductive reference modeling may contribute to the trend of combining BPM with arti cial intelligence (AI)2.
Until a few years ago, although inductive development was generally
acknowledged, the literature on methods for reference model development was dominated
by deductive approaches. This is interesting, as many existing reference models
were at least partially developed inductively [
When applying reference model mining (RMM), i.e. (semi-)automatic
inductive reference model development, it becomes evident that the reference model
content and character are signi cantly in uenced by the choice of mining
technique and its parametrization. Di erent mining techniques yield di erent models,
even when applied to the same set of input models. Meanwhile, given a
reuseoriented understanding of reference models, the requirements to the reference
model are determined by the situational context it will be used in, similar to the
adaptation of software developments methods in Situational Method Engineering
(SME) [
Designing a method for S-RMM and understanding the in uencing factors behind it is the main objective of the presented dissertation project titled \Situational Reference Model Mining | Conceptual Design and Selected Applications", which is conducted at the Institute of Information Systems at Saarland University, under the supervision of Prof. Dr. Peter Loos. It started in October 2015 and is planned to be completed in 2020. Some preliminary results and cited publications were already achieved during the author's time as research assistant at the same institute (April 2011 until October 2015).
2Cf. the keynote speech \Intelligent Continuous Improvement, When BPM Meets AI" by Miguel Valdes at BPM 2017 Reference Model Design Requirements Choice of Technique
Design
Principle Individual Models Target Models
Research Method and Research Questions
As the main objective of the project is the design of an artifact (a method
for S-RMM), it follows the design science research paradigm (DSR), originally
coined by Hevner et al. [
This goal shall be reached by answering the following four research questions. The rst two questions are knowledge questions, determined to gather knowledge on the reference modeling process. The second two questions are design questions, asking for new artifacts to improve the reference modeling process. 1. Which contextual factors in uence reference model design? 2. Which techniques exist for reference model mining and which contextual factors in uence their choice and applicability? 3. How can reference model mining techniques be matched with situational contexts to produce applicable reference models? 4. How can reference model mining be applied in a given application case, considering situational contextual factors?
The rst question addresses the contextual factors that in uence reference modeling. It is an open descriptive empirical research question, meant to observe reference modeling in real-world scenarios, gathering knowledge about the context of the artifact to be designed without the need for explanations. In contrast, the second question is an open explanatory empirical knowledge question with the goal to identify existing RMM techniques and to determine their potentials and limitations. We want to know under which situational circumstances a certain technique may and may not produce an applicable and well-suited reference model. Because these circumstances may apply to multiple techniques, they should be conclusively explained by the technique's properties. Treatment Implementation
Treatment Validation How does this artifact contribute to stakeholder goals?
Problem Investigation What must be improved? Why? Treatment Design Which artifact could solve the problem?
The third question joins the existing artifacts (i.e. the RMM techniques) with the context by designing a method to match an existing technique with a situational context, such that the produced reference models are applicable and useful for their intended purpose. Therefore, the results from the previous two questions need to be related to each other through some intermediary concept. This concept and the matching method are then used in the fourth question, which nally addresses the overall goal of the dissertation project, as sketched by the template above. It is set out to design a comprehensive method for SRMM, ranging from the identi cation of a need for a new reference model to its application and validation in a concrete use case.
Knowledge questions and design questions are answered by means of di erent
research methods, following Wieringa's design cycle [12, p.27 .] in Fig. 2 and
Frank's pluralistic conception of research methods in IS research [
The concept of situational reference model construction based on design
principles is not new, but has yet only been elaborated for deductive reference model
development [
The term \context" can be de ned as \any information that can be used to
characterize the situation of an entity" [
S-RMM is innovative in the way that it combines the domain of reference modeling with the idea to adapt an artifact to the context in which it is used, as coined by SME, and techniques to derive a process model from collected real-life data, as in process mining. Giving a manual procedure model for inductive reference modeling based on RMM techniques, S-RMM goes beyond SME, because it does not directly in uence the artifact itself (the model), but instead adapts the method used for deriving it. It di ers from process mining, as both process models and execution logs are considered potential data sources. To our knowledge, no comparable approaches or solutions exist in state-of-the-art literature. 4
Whereas most of the author's contributions have so far addressed research
question 2 (e.g [
Considering a model construction process, there exist several di erent
techniques for deriving a conceptual model from another one. These so-called design
4This section is based on previous work presented in [
Determine Situational Context
Determine Target Model Design
Principle Design For Reuse Design With Reuse
Choose Mining
Technique
Choose Input Models
Mine
Reference Model
Adapt Reference Model
Design Target Models
Evaluate
Target Models
principles describe how the content of the original model is adopted, adapted,
and extended in order to create a new model. Five design principles are described
in the literature [
The main idea behind our method for S-RMM is to match RMM techniques with applicable contexts by means of selecting appropriate design principles for the construction of both target and reference models. Depending on the situational circumstances and the target model requirements, a certain design principle is applied to derive the target model from the reference model. This design principle poses certain restrictions and requirements to the reference model design, which is mainly in uenced by the choice of technique that was used to mine the reference model. Hence, the choice of mining technique is ultimately determined by the situational context of the reference model application.
Research question 4 is addressed by the rst conceptual design for a procedure model for S-RMM, shown in Fig. 3. It constitutes the main artifact to be delivered in the dissertation. It is designed around the conceptualization of S-RMM in Fig. 1 and describes a generic execution process of an S-RMM application. Of the ten steps, seven belong to DFR and focus on the reference model construction (i.e. the actual mining), whereas three belong to DWR and are concerned with the target model construction (i.e. the reference model application).
The procedure model starts with de ning the situational context, which determines the target model design principle in the second step. As stated below, this step is not yet conclusively elaborated and requires a lot of additional research. In the third step, the reference model requirements are de ned, which are partly determined by the used principle and partly by the context itself. The reference model design principle is derived from these requirements, with the help of additional methods and artifacts, as explained below. For certain combinations of target model and reference model principle, several mining techniques are available; their choice may depend on additional factors. The input models can only be nally selected after the mining technique, as some techniques pose additional requirements to their input data. Afterwards, the model can be mined, concluding the DFR process. In the DWR process, the model is manually or automatically adapted, before the target models can be derived and evaluated regarding their purpose.
To provide a guideline for applying the procedure model and to answer
research question 3, we analyzed existing mining techniques regarding their
underlying principles and requirements (cf. Table 1). For each target model design
principle, we suggest corresponding reference model design principles and, for
each pair, a example of a suitable mining technique. A more detailed version of
this table, classifying many state-of-the-art techniques can be found in [
To conclusively answer research question 2, it is necessary to update the
literature analysis from [
Our analysis of matching existing RMM techniques with accepted design principles for reference models in Tab. 1 is a preliminary sketch of a conclusive answer to research question 3. It needs to be complemented by additional principles such as modi cation, elimination, or union, potentially by means of a structuring framework. The RMM techniques identi ed in the previous research question need to be matched the the individual principles. Most importantly, there needs to be some matching procedure between the context factors from the rst question to the design principles, and then, the RMM techniques.
The procedure model in Fig. 3 is the framework for an answer to research question 4. Not only does it require an in-depth analysis of posed requirements and an according adaptation and re nement, it also has to be substantiated by concrete operationalizations of the individual stages. At this point, it is unclear how the stages should be executed. To complete the design cycle, the procedure model is supposed to be evaluated in practical case studies, where it is used to inductively develop a reference model for a certain context. These case studies have yet to be determined, planned, and executed.