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AN EXECUTION-SEMANTIC APPROACH TO INDUCTIVE REFERENCE MODEL DEVELOPMENT
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Reference models are a cost-and time-saving approach for the development of new models. As induc-tive strategies are capable of automatically deriving a potential reference process model from a collection of existing process models, they have gained attention in current research. A number of promising approaches can be found in recent publications. However, all existing methods rely on graph-based similarity measures to identify commonalities between input models. Since behaviourally similar process models can have different graphical structures, those approaches are unable to find certain commonalities. To overcome these shortcomings, we propose a new approach to inductive reference model development based on an execution-semantic similarity measure. Since a naïve solution to the intuitive idea does not yield productive results, the proposed approach is rather elaborate. By capturing the commonalities of the input models in a behavioural profile, we are able to derive a reference model subsuming the input models' semantics instead of their structure. In our contribution, this approach is outlined, implemented and evaluated in three different scenarios. As the evaluations show, it is capable of handling complex process models and overcome most restrictions that structural approaches pose. Thus, it introduces a new level of flexibility and applicability to inductive reference modelling.
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... In the next step, we mine a reference process model for each of the identified clusters. Therefore, we adapt our own approach to inductive reference model development, based on the execution semantics of a given set of process models [9]. As process traces are a representation of the intended semantics of a reference model, the RMM-2 approach is suitable for our use case. ...
... These profiles are then used to derive the reference model. The reader is referred to the original publication for details on its definition and implementation [9]. The result of this step is a collection of reference models, which are ordered in a hierarchical way, analogous to the cluster structure from the previous step. ...
Reference models provide generic blueprints of process models that are common in a certain industry. When designing a reference model, stakeholders have to cope with the so-called ‘dilemma of reference modeling’, viz., balancing generality against market specificity. In principle, the more details a reference model contains, the fewer situations it applies to. To overcome this dilemma, the contribution at hand presents a novel approach to mining a reference model hierarchy from large instance-level data such as execution logs. It combines an execution-semantic technique for reference model development with a hierarchical-agglomerative cluster analysis and ideas from Process Mining. The result is a reference model hierarchy, where the lower a model is located, the smaller its scope, and the higher its level of detail. The approach is implemented as proof-of-concept and applied in an extensive case study, using the data from the 2015 BPI Challenge.
... The second approach is based on the analyses and application of real-world data, classification and information retrieval techniques. In [8], a new approach to inductive reference model development is proposed. This method is based on an executionsemantic similarity measure and capturing the commonalities of the input models in a behavioral profile. ...
The individualization of information processes based on artificial intelligence (AI), especially in the context of industrial tasks, requires new, hybrid approaches to process modeling that take into account the novel methods and technologies both in the field of semantic representation of knowledge and machine learning. The combination of both AI techniques imposes several requirements and restrictions on the types of data and object properties and the structure of ontologies for data and knowledge representation about processes. The conceptual reference model for effective individualization of information processes (IIP CRM) proposed in this work considers these requirements and restrictions. This model is based on such well-known standard upper ontologies as BFO, GFO and MASON. Evaluation of the proposed model is done on a practical use case in the field of precise agriculture where IoT-enabled processes are widely used. It is shown that IIP CRM allows the construction of a knowledge graph about processes that are surrounded by unstructured data in soft and heterogeneous domains. CRM also provides the ability to answer specific questions in the domain using queries written with the CRM vocabulary, which makes it easier to develop applications based on knowledge graphs.
... Compared to the other three requirements, FRQ4 is the most diverse in terms of degree of fulfillment. A group of researchers around Fettke and Loos proposes several methods that are explicitly tailored to work with event-driven process chains (EPC) [18,19,38], while authors like Leng and Jiang [35] focus on a specific representation of service processes. Other studies, such as [33] and [40], are less restrictive but also more ambiguous regarding the modeling language used, as they provide formal or informal specifications of how business process models should look and do not explicitly map these specifications to a specific notation. ...
Business process management often uses reference models to improve processes or as starting point when creating individual process models. The current academic literature offers primarily deductive methods with which to develop these reference models, although some methods develop reference models inductively from a set of individual process models, focusing on deriving and representing common practices. However, there is no inductive method with which to detect best practices and represent them in a reference model. This paper addresses this research gap by proposing a method by which to develop reference process models that represent best practices in public administrations semi-automatically and inductively. The method uses a merged model that retains the structure of the source models while detecting their common parts. It identifies best practices using query constructs and ranking criteria to group the source models’ elements and to evaluate these groups. We provide a conceptualization of the method and demonstrate its functionality using an artificial example. We describe our implementation of the method in a software prototype and report on its evaluation in a workshop with domain and method experts who applied the method to real-world process models.
... Their authors explicitly state that they were specifically developed for certain model structures like EPCs [34], WS-BPEL [26] or Workflow Nets [33]. Some focus on the analysis of process models' control flow [25,37] and, thus, cannot be applied to EA model structures. The remaining approaches were dismissed due to major adjustments one would have to make using them for EA 6 model structures. ...
Enterprise architectures (EA) help organizations to analyze interrelations among their strategy, business processes, application landscape and information structures. Such ambitious endeavors can be supported by using reference models for EA. In recent years, research has increasingly been investigating inductive methods for reference model development. However, the characteristics of EA models have not been considered in this context yet. We therefore aim to adapt existing inductive approaches to the domain of reference enterprise architectures development. Using design science research our work contributes to the reference modeling community with (i) a comparative analysis of inductive reference modeling methods regarding their applicability to EA models, (ii) the refinement of an identified approach to reference EA design and (iii) its application in a use case.
... Das Referenzmodell wird im Referenzmodell entwickelt, indem Gemeinsamkeiten der individuellen Modelle identifiziert werden und von den Besonderheiten abstrahiert wird. Eine zunehmende Abstraktion von den Spezifika der individuellen Unternehmensmodelle ist Merkmal des Entwicklungsprozesses.In jüngster Zeit sind insbesondere Konzepte, Methoden und Werkzeuge zur induktiven Referenzmodellierung entwickelt und erforscht worden[Rehse et al. 2016]. Ein Beispiel ist der am Deutschen Forschungszentrum für Künstliche Intelligenz (DFKI) entwickelte RefMod-Miner, der vielfältige Funktionen zur Referenzmodellentwicklung zur Verfügung stellt. ...
Das zentrale Charakteristikum eines Referenzmodells ist seine intendierte bzw. faktische Wiederverwendung. Damit ist ein Referenzmodell ein Modell, das zur Wiederverwendung empfohlen oder faktisch zur Konstruktion weiterer Modelle wiederverwendet wird.
Bisher hat sich innerhalb der Forschung zur Referenzmodellierung keine allgemein anerkannte Definition des Terminus Referenzmodell herausgebildet. Allerdings lässt sich in jüngster Zeit eine Konvergenz verschiedener terminologischer Bestimmungen in Richtung eines wiederverwendungsorientierten Referenzmodellbegriffs feststellen. Zur weiteren Systematisierung und unterschiedlichen Begriffsauffassungen siehe [Fettke, Loos 2004; Fettke 2006; Fettke, Loos 2007; vom Brocke 2003].
The paper motivates, presents, demonstrates in use, and evaluates a methodology for conducting design science (DS) research in information systems (IS). DS is of importance in a discipline oriented to the creation of successful artifacts. Several researchers have pioneered DS research in IS, yet over the past 15 years, little DS research has been done within the discipline. The lack of a methodology to serve as a commonly accepted framework for DS research and of a template for its presentation may have contributed to its slow adoption. The design science research methodology (DSRM) presented here incorporates principles, practices, and procedures required to carry out such research and meets three objectives: it is consistent with prior literature, it provides a nominal process model for doing DS research, and it provides a mental model for presenting and evaluating DS research in IS. The DS process includes six steps: problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication. We demonstrate and evaluate the methodology by presenting four case studies in terms of the DSRM, including cases that present the design of a database to support health assessment methods, a software reuse measure, an Internet video telephony application, and an IS planning method. The designed methodology effectively satisfies the three objectives and has the potential to help aid the acceptance of DS research in the IS discipline.
Business Process Management is an important topic in the Business Informatics field and organizations develop and use business process models as a fundament for their practical operations. However, despite the maturity of business process model concepts and different approaches for merging, integrating and dividing business process models or creating reference models, evaluation and analysis of these approaches has remained a challenge. This problem is mainly caused by the importance of process models and companies avoidance to make their private data public. In order to overcome this challenge, we present an EPC Generator concept to generate different process models based on a real business process model. These generated models can be configured according to their usage and user preferences and are alternatives for real business process models. Moreover, we have implemented a prototype based on this concept to demonstrate the feasibility of our approach.
Business Process Modeling has become a major task in the field of Business Process Management. There has been a trend within organizations towards adapting and reusing existing reference models for the modeling of individual business processes that belong to the same application domain to save time and costs. Due to the high availability of individual business process models together with the need for further reference models, the inductive develop-ment of reference models has gained tremendous importance. Meanwhile, different heuristic approaches have been proposed to the research community, based on median graph computation. By way of contrast, our approach tries to derive reference models based on factor analysis, which does not require an approximated matching between the individual business processes as an additional level of abstraction. The results of the described approach are compared to the results of an existing heuristic approach for a qualitative evaluation of both inductive development concepts.
With the growth of the Business Process Management (BPM) market, cus-tomer requirements based process customization has emerged as a key to competitive advantage. Where there are numerous demands for customization, a great number of business process model variations result. The existence of numerous process variations leads to both process redundancy and process underutilization, which impact on business performance in negative ways. Thus, there is a need to create a process reference model that can identify and find a representative model without redundancy. This paper intro-duces a new, Genetic Algorithm (GA)-based approach to generation of a valid business process reference model from a process repository. Previous research using the integer programming (IP) problem produced a reference process model. However, there are prob-lems, pertaining to presentational limitations and unguaranteed validation processes. The GA procedure uses the randomness of genetic processes to resolve both problems in IP formulation. Near the end of this paper, we show the experimental results of the proposed method, which is conveniently executed using business process structure properties and the proximity of activities. It is believed that this process reference model can help a novice process designer to create a new process based on existing processes.
The implementation of business process management (BPM) systems in large number of business organizations transforms BPM system into such a level of maturity and tends to collect large repositories of business process (BP) models. This issue encourages BP flexibility that leads to a large number of process variants derived from the same model, but differing in structure, to be stored in the large repositories of BP models. Therefore, the repositories may include thousands of activities and related business objects with variation of requirements and quality of service. It is a common practice to customize processes from reference processes or templates in order to reduce the time and effort required to design and deploy processes on all levels. In order to address redundancy and underutilization problems, a generic process model, called as reference BP, is absolutely necessary to cover the best of process variants. This study aims to develop multiple-objective business process genetic algorithm (MOBPGA) to find a set of non-dominated (Pareto) solutions of business reference model to enhance conventional approach which considered only a single objective on creating BP reference model by using proximity score measurement. A mixed-integer linear program is constructed to evaluate performance of the proposed MOBPGA on small-scale problems by using standard measures for multiple-objective techniques. The results will show the viability of applying MOBPGA in terms of simultaneously maximizing proximity score measurement, minimizing total duration, and total costs of the selected reference model.
Information Systems (IS) research. Based on the growing maturity of its concepts, methods and techniques BPM has, furthermore, gained tremendous importance in organizational practice. More and more organizations develop and use individual business process models as a fundament for their operations. As the development of individual business process models is a complex and expensive endeavour, organisations aim at reusing and adapting already existing business process models, so called reference models. However, so far only a limited amount of reference models for selected domains exist, which makes the development of new and reliable reference models a highly relevant issue. In this contribution, we present a new heuristic approach for the inductive development of reference process models based on existing individual process models. Our approach focuses on minimal cost of change (MCC) (based on minimal graph edit distance) when adapting the developed reference model to match the underlying individual process models. Furthermore, an according software prototype supporting automated inductive reference model development is presented as a proof of concept. Finally, our approach is compared to other state of the art approaches in this field in order to qualitatively evaluate its feasibility and usefulness.
Configurable process models can be used to encode a multitude of (different) process models. After configuration, they can be used to support the execution of a particular process. A configurable process model represents a space of instantiations (configured process variants). Such an instantiation space can be used by an organisation to select the best instantiation(s) according to some Key Performance Indicators (KPIs), e.g., cost, throughput time, etc. Computing KPIs for all the instantiations in the space is time consuming, as it might require the analysis (e.g., simulation) of thousands (or more) of instantiations. Therefore, we would like to exploit structural characteristics to reduce the amount of instantiations which need to be analysed. This reduction only removes those instantiations which do not need to be considered by an organisation. This yields the same result (a collection of best configurations), but in a faster way.
Conceptual models play an increasingly important role in all phases of the information systems life cycle. For instance, they are used for business engineering, information systems development and customizing of enterprise resource planning (ERP) systems. Despite conceptual modeling being a vital instrument for developing information systems, the modeling process often is resource consuming and faulty. As a way to overcome these failures and to improve the development of enterprise-specific models, the concept of reference modeling has been introduced. A reference model is a conceptual framework and may be used as a blueprint for information systems development. In this chapter, we seek to motivate research on reference modeling and introduce the chapters of this book on using reference models for business systems analysis. Our discussion is based on a framework for research on reference modeling that consists of four elements: reference modeling languages, reference modeling methods, reference models and reference modeling context. Each element of the framework is discussed with respect to prior research, the contributions of chapters in this book and future research opportunities.
Business process management is one of the most widely discussed topics in information systems research. As process models advance in both complexity and maturity, reference models, serving as reusable blueprints for the development of individual models, gain more and more importance. Only a few business domains have access to commonly accepted reference models, so there is a widespread need for the development of new ones. This article describes a new inductive approach for the development of reference models, based on existing individual models from the respective domain. It employs a graph-based paradigm, exploiting the underlying graph structures of process models by identifying frequent common subgraphs of the individual models, analyzing their order relations, and merging them into a new model. This newly developed approach is outlined and evaluated in this contribution. It is applied in three different case studies and compared to other approaches to the inductive development of reference models in order to highlight its characteristics as well as assets and drawbacks.