Philipp Diefenthaler’s research while affiliated with University of Augsburg and other places

Enterprise architecture (EA) management supports transformation path planning to facilitate the change from the current to the target architecture. We create parts of these transformation paths automatically using the information from current and target business support maps. Restrictions on the business support maps, i.e. areas which shall remain stable and which shall be transformed, are modeled by an enterprise architect to allow for a goal oriented transformation path generation. The transformation paths serve as project proposals for the project portfolio management. Necessary changes to the EA are prioritized and estimated. Our solution uses a graph transformation based approach to allow for an interactive creation of possible transformation paths. The transformation paths are the state transitions of a graph transition system, which we create from an EA model. We weigh the effort of each transformation according cost, time and risk.

Wir präsentieren eine Lösung für das Business-IT-Alignment in Unternehmen, um eine solide Informationsbasis für fundierte und sichere Entscheidungen aufzubauen. Die Grundlage dazu findet sich in einer semantischen Unternehmensarchitektur, einem ganzheitlichen, formalen Modell der zentralen Artefakte eines Unternehmens und ihrer Beziehungen. Semantic Enterprise Architecture Management setzt semantische Technologien ein, um Unternehmensarchitekturen formal zu modellieren, vorhandene Datenquellen direkt darin zu integrieren und auf dieser Basis komplexe Analysen oder auch die automatisierte Planung von Veränderungen in IT-Landschaften zu unterstützen. Der Einsatz semantischer Technologien reduziert den Aufwand für den Aufbau einer Unternehmensarchitektur und gewährleistet gleichzeitig die Aktualität und Konsistenz der bereitgestellten Informationen. Die Formalisierung der Unternehmensarchitektur macht die dort vorliegenden Informationen auch für neuartige intelligente Werkzeuge nutzbar.

Planning changes in an enterprise and its supporting IT can be supported by enterprise architecture (EA) models. The planned changes result in gaps which can be derived by a gap analysis. But, knowing the gaps is not enough. Also important is to know in which sequence gaps are to be closed for transformation path planning. In this paper we show how gaps are identified and reused for detailing a model of the target architecture. Based on this refinement further gaps become visible. Furthermore, we describe how it is possible to create with a transformation model and an action repository transformation paths towards a desired and detailed target architecture. Afterwards, we give a use case example and propose a technical realization of the solution.

Enterprises have to react to changes with an increasing speed in order to stay competitive. Many approaches support the modeling of enterprise architectures but lack an evolution of enterprise architectures through demonstrating a transformation path from one architecture state to another. Enterprises know their strategic goals and are able to model them, but are not supported towards achieving these goals in terms of developing their architecture. We want to improve the current manual creation of the transformation paths in enterprise architecture planning by providing possible and sound sequences of actions as part of a roadmap from the current to a desired target architecture. Therefore, we present a solution that supports the enterprise architect with proposals for a transformation path from the current to the target state considering dependencies to be taken into account during the enterprise transformation.

Enterprise architecture management (EAM) provides information about an enterprise and its information systems landscape for thorough analysis. Semantic technologies allow for integrating data sets from various relevant information sources within enterprises in a so-called EA repository, which serves as a comprehensive formal information base for EAM. We call this approach Semantic Enterprise Architecture Management, SEAM for short. We show how SEAM uses semantic technologies to bridge the heterogeneity between various data sets relevant for EAM, such as The Open Group Architecture Framework (TOGAF) models, Business Process Modeling Notation (BPMN) business process models and Service-oriented Architecture (SOA) models. Query answering and reasoning enable detailed analysis and consistency checks on the SEAM repository in order to discover complex dependencies and implicit knowledge.