Service architecture design for E-Businesses: A pattern-based approach

E-business involves the implementation of business processes over the Web. At a technical level, this imposes an application integration problem. In a wider sense, the integration of software and business levels across organisations becomes a significant challenge. Service architectures are an increasingly adopted architectural approach for solving Enterprise Applications Integration (EAI). The adoption of this new architectural paradigm requires adaptation or creation of novel methodologies and techniques to solve the integration problem. In this paper we present the pattern-based techniques supporting a methodological framework to design service architectures for EAI. The techniques are used for services identification, for transformation from business models to service architectures and for architecture modifications

APQL: A process-model query language

As business process management technology matures, organisations acquire more and more business process models. The management of the resulting collections of process models poses real challenges. One of these challenges concerns model retrieval where support should be provided for the formulation and efficient execution of business process model queries. As queries based on only structural information cannot deal with all querying requirements in practice, there should be support for queries that require knowledge of process model semantics. In this paper we formally define a process model query language that is based on semantic relationships between tasks in process models and is independent of any particular process modelling notation

Requirements Catalog for Business Process Modeling Recommender Systems

The manual construction of business process models is a time-consuming and error-prone task. To improve the quality of business process models, several modeling support techniques have been suggested spanning from strict auto-completion of a business process model with pre-defined model elements to suggesting closely matching recommendations. While recommendation systems are widely used and auto-completion functions are a standard feature of programming tools, such techniques have not been exploited for business process modeling although implementation strategies have already been suggested. Therefore, this paper collects requirements from different perspectives (literature and empirical studies) of how to effectively and efficiently assist process modelers in their modeling task. The condensation of requirements represents a comprehensive catalog, which constitutes a solid foundation to implement effective and efficient Process Modeling Recommender Systems (PMRSs). We expect that our contribution will fertilize the field of modeling support techniques to make them a common feature of BPM tools

B-BabelNet: Business-Specific Lexical Database for Improving Semantic Analysis of Business Process Models

Similarity calculation between business process models has an important role in managing repository of business process model. One of its uses is to facilitate the searching process of models in the repository. Business process similarity is closely related to semantic string similarity. Semantic string similarity is usually performed by utilizing a lexical database such as WordNet to find the semantic meaning of the word. The activity name of the business process uses terms that specifically related to the business field. However, most of the terms in business domain are not available in WordNet. This case would decrease the semantic analysis quality of business process model. Therefore, this study would try to improve semantic analysis of business process model. We present a new lexical database called B-BabelNet. B-BabelNet is a lexical database built by using the same method in BabelNet. We attempt to map the Wikipedia page to WordNet database but only focus on the word related to the domain of business. Also, to enrich the vocabulary in the business domain, we also use terms in the business-specific online dictionary (businessdictionary.com). We utilize this database to do word sense disambiguation process on business process model activity’s terms. The result from this study shows that the database can increase the accuracy of the word sense disambiguation process especially in particular terms related to the business and industrial domains

Continuous Quality Improvement of IT Processes based on Reference Models and Process Mining

The inherent quality of business processes increasingly plays a significant role in the economic success of an organization. More and more business processes are supported through IT processes. In this contribution, we present a new approach which allows the continuous quality improvement of IT processes by the interconnection of IT Infrastructure Library (ITIL) reference model and process mining. On the basis of the reference model, to-be processes are set and key indicators are determined. As-is processes and their key indicators derived by process mining are subsequently compared to the to-be processes. This new approach enables the design and control of ITIL based customer support processes which will be trialed in a practice case of a customer relationship management (CRM) system. The procedural models, as well as its results, are introduced in this publication

Semantic Benchmarking of Process Models - An Ontology-Based Approach

This article suggests an approach which allows the costly analysis of processes (e.g., in serviceoriented architectures) for benchmarking to be partially automated, so that the performance indicators, as well as qualitative differences between processes become apparent. The approach is based on using appropriate ontologies, which make the process models both syntactically and semantically comparable. In this article, we present a conceptual model for this new approach to process benchmarking, a framework, as well as a software prototype for analyzing and comparing individual process models. We provide an overview of our multi-method evaluation methodology and delineate the technical, conceptual, and economic evaluation perspectives with their respective outcomes. This analysis allowed us to determine whether our approach is generally suitable for generating novel and useful information on different process models that describe the same problem domain

Identifying Business Process Activity Mappings by Optimizing Behavioral Similarity

This paper describes an approach designed to create a mapping between corresponding activities from two business processes that is geared towards handling noisy similarity values for the labels describing these activities. This is achieved by formulating an optimization problem – maximize the behavioral similarity of the processes as a whole – whose target value depends on the mapping. Thereby, the mapping is created not only with respect to label similarities but also with respect to the overall control flow structure, which avoids some mistakes resulting from erroneous label similarities. A preliminary evaluation demonstrates the improvement

Corpus Statistics for Measuring Business Process Similarity

In a rapidly changing environment, organizations must adapt their business processes continuously. While numerous methods enable enterprises to conceptualize and analyze their organizational structure, the task of business process modeling remains complex and time-consuming. However, by reusing and adapting existing process models, enterprises can reduce the task’s complexity while improving the quality of results. To facilitate the identification of adaptable processes, several techniques of business process similarity (BPS) have been proposed in recent years. Although most approaches produce sound results in controlled evaluations, this paper argues that their applicability is limited when analyzing real-world processes, which do not fully comply with notational labeling specifications. Consequently, we aim to enhance existing BPS techniques by using corpus statistics to account for the explanatory power of words within labels of process models. Results from our evaluation suggest that corpus statistics can improve BPS computations and can positively influence the quality of practical implications