Effects of Semantic Quality in Business Process Modeling

In contrast to the increasing meaning of business process management (BPM), there is a lack of knowledge about processes that impedes their analysis, implementation, and execution in business process management systems (BPMS). In this context, process modeling is an opportunity to capture process knowledge. Nevertheless, models are incomplete concerning semantic completeness. Therefore, ontologies as explicit and formal specification are used to enrich models semantically to achieve a high degree of semantic quality, model efficiency and effectiveness. But also ontology engineering needs models to describe the underlying discourse of universe. For this reason, it is the paper’s goal to examine and compare the Resource Event Agent Model (REA) with respect to semantic quality, model effectiveness, and -efficiency in data modeling for ontologies. Moreover, the paper addresses the research question, if REA enables an effective modeling to reduce the precision deficit and complexity in BPM. Keywords (Required

Integrated Information Supply for Decision Support in Grid Companies

Increasing regulatory requirements such as price cap regulation have increased the importance of strategic grid asset management. Empirical studies reveal that information supply and consolidation are error prone and long-term processes. The reason is the missing automation of extraction, transformation, and loading. The current gap does neither fulfill the requirements of regulatory nor the necessity of standardized reporting. Furthermore, a detailed planning is not enabled and the calculation of key figures is extensive. Currently, a framework that considers the coupling of financial and technical key figures, the coupling of strategic and operative key figures as well as the integration into information systems is not existent. Therefore, this paper addresses the design of a reference model as a recommendation for action to integrate the asset management within information systems. It is validated by expert interviews. Moreover, it provides information to integrate relevant financial and technical artifacts from distributed systems. Simultaneously, it provides recommendations for implementing a Business Intelligence architecture in the context of strategic decision support

ONTOLOGICAL ANALYSIS OF VALUE MODELS

The current lack of consistency between business processes and their underlying business models lead to a lack of understanding about business process contribution to the value chain. In order to enhance understanding of business models and their impacts to business processes, consistency of value model representations is one important aspect. Examining representations - i.e. e³value, Resource Event Agent model, and the Business Object Model -concerns both grammar and method. Therefore, the paper presents in a first step an ontologic grammar evaluation of value models, which bases on the Bunge Wand Weber Representation Model. By examining conceptual representations using e³value, UML class diagram and ER modelling in context of value models, their impact to business processes is analysed evaluating the expressiveness in terms of ontologic coverage and overlap. Impact refers to the ability to transform the concepts of value models to the process level. The paper’s contribution is not the overall evaluation, but the proof of appropriateness of value modelling grammars to their potential of an enhanced user understanding