Andreas Schoknecht

Report : The Process Model Matching Contest 2013

Process model matching refers to the creation of correspondences between activities of process models. Applications of process model matching are manifold, reaching from model validation over harmonization of process variants to effective management of process model collections. Recently, this demand led to the development of different techniques for process model matching. Yet, these techniques are heuristics and, thus, their results are inherently uncertain and need to be evaluated on a common basis. Currently, however, the BPM community lacks established data sets and frameworks for evaluation. The Process Model Matching Contest 2013 aimed at addressing the need for effective evaluation by defining process model matching problems over published data sets.

Similarity of Business Process Models—A State-of-the-Art Analysis

Business process models play an important role in today’s enterprises, hence, model repositories may contain hundreds of models. These models are, for example, reused during process modeling activities or utilized to check the conformance of processes with legal regulations. With respect to the amount of models, such applications benefit from or even require detailed insights into the correspondences between process models or between process models’ nodes. Therefore, various process similarity and matching measures have been proposed during the past few years. This article provides an overview of the state-of-the-art regarding business process model similarity measures and aims at analyzing which similarity measures exist, how they are characterized, and what kind of calculations are typically applied to determine similarity values. Finally, the analysis of 123 similarity measures results in the suggestions to conduct further comparative analyses of similarity measures, to investigate the integration of human input into similarity measurement, and to further analyze the requirements of similarity measurement usage scenarios as future research opportunities.

A Comprehensive Overview of Visual Design of Process Model Element Labels

Process model element labels are critical for an appropriate association between a symbol instance in a model and the corresponding real world meaning. Disciplines, in which an efficient presentation of text labels is crucial (e.g., cartography) have continuously improved their visualization design techniques for labels since they serve as effective cognitive aids in problem solving. Despite the relevance of labels for information exploration, surprisingly little research has been undertaken on the visual design of element labels of business process models. This paper fills this gap and provides a comprehensive overview of visual design options for process model element labels. First, we summarize the findings existing in the diverse areas of literature relevant to visual display of process model element labels. Second, we analyze the status quo of visual design of element labels in common business process modeling tools indicating only little layouting support. Third, we give recommendations regarding the visual design of element labels. To our knowledge, this is the first comprehensive analysis of visual design of process model element labels.

A Comparative Analysis of Business Process Model Similarity Measures

To work efficiently with and unlock the potentials of business process models, measuring their similarity is a basic requirement. Thus, many automatic similarity measurement approaches have been developed during the last years, which utilize very different aspects of a model. At the same time, it is unclear which measures can be meaningfully applied in which context and how they behave in general. Hence, this paper analyzes how the values of existing similarity measures correlate and how corresponding implementations perform with respect to their resource consumption. The results of our analysis show that the similarity values of most measures highly correlate while their performance prohibits the usage of more than 50% of the measures in practice.

Process Model Search Using Latent Semantic Analysis

Process model similarity measures can be utilized for searching process model collections, which is also called similarity-based search. While there are quite a lot of approaches, most of them base on an underlying alignment between the activities of the compared process models. Yet, according to the results of the process model matching contests conducted in recent years, such an alignment seems to be quite difficult to achieve. The Latent Semantic Analysis-based Similarity Search approach described in this paper circumvents the matching challenge by not requiring such a matching. Instead, it uses a Latent Semantic Analysis-based Similarity Measure to query model collections and retrieve similar models. An evaluation with a collection of 80 models resulted in very good results in terms of Precision, Recall, and F-Measure. The best F-Measure value obtained during the experiments was 0.92.

Security in a Distributed Key Management Approach

Cloud computing offers many advantages as flexibility or resource efficiency and can significantly reduce costs. However, when sensitive data is outsourced to a cloud provider, classified records can leak. To protect data owners and application providers from a privacy breach data must be encrypted before it is uploaded. In this work, we present a distributed key management scheme that handles user-specific keys in a single-tenant scenario. The underlying database is encrypted and the secret key is split into parts and only reconstructed temporarily in memory. Our scheme distributes shares of the key to the different entities. We address bootstrapping, key recovery, the adversary model and the resulting security guarantees.

LS3: Latent Semantic Analysis-based Similarity Search for Process Models

Please note that due to an editorial mishap, the PDF of this publication had to be changed on 2017-10-19 (marked as ‘corrected version’). Large process model collections in use today contain hundreds or even thousands of conceptual process models. Search functionalities can help in handling such large collections for purposes such as duplicate detection or reuse of models. One popular stream of search functionalities is similarity-based search which utilizes similarity measures for finding similar models in a large collection. Most of these approaches base on an underlying alignment between the activities of the compared process models. Yet, such an alignment seems to be quite difficult to achieve according to the results of the Process Model Matching contests conducted in recent years. Therefore, the Latent Semantic Analysis-based Similarity Search (LS3) technique presented in this article does not rely on such an alignment, but uses a Latent Semantic Analysis-based similarity measure for retrieving similar models. An evaluation with 138 real-life process models shows a strong performance in terms of Precision, Recall, F-Measure, R-Precision and Precision-at-k, thereby outperforming five other techniques for similarity-based search. Additionally, the run time of the LS3 query calculation is significantly faster than any of the other approaches.

Using the Horus Method for Succeeding in Business Process Engineering Projects

This chapter presents the Horus Method for business process engineering, which is divided into four phases. These four phases consist of (1) an initial project preparation phase; (2) a strategy and architecture phase for the definition of strategic aspects as well as enterprise and system architecture; (3) a business process analysis phase; and (4) an application phase for the actual usage of models, thereby covering essential aspects of business process engineering. A formal conceptualization of the Horus Method is provided using the FDMM formalism, which is used for tool specification for the ADOxx platform. Thereby, the focus is on the formalization of XML nets, a special variant of high-level Petri Nets, for the modeling of interorganizational business processes in the field of e-commerce. Finally, a real-life case study is described which highlights the capabilities of the Horus Method for successful business process engineering projects.

A Taxonomy and Catalog of Business Process Model Patterns

While a large number of business process model patterns have been suggested in the literature, it is currently difficult to find patterns that might be useful in a given context. The reason is that the relevant publications are spread in various journals and other types of publications, and there is no guidance for locating a pattern that can be useful for solving a given problem. In our article, we present the results of a literature survey that has been conducted with the aim to get an exhaustive overview on existing publications on business process modeling patterns. The results of the survey allowed us to propose a taxonomy of existing patterns as a first step towards a pattern language of business process model patterns. Furthermore, we created an online catalog that allows finding publications on business process model patterns based on various search criteria. It is intended to be useful both for business process modeling practitioners as for researchers in need of sound literature references. Currently, this catalog includes links to 89 publications (usually containing more than one pattern). It is our aim to populate the catalog with patterns published in the future.