Dierk Jugel

Digital Enterprise Architecture - Transformation for the Internet of Things

Excellence in IT is both a driver and a key enabler of the digital transformation. The digital transformation changes the way we live, work, learn, communicate, and collaborate. The Internet of Things (IoT) fundamentally influences todays digital strategies with disruptive business operating models and fast changing markets. New business information systems are integrating emerging Internet of Things infrastructures and components. With the huge diversity of Internet of Things technologies and products organizations have to leverage and extend previous Enterprise Architecture efforts to enable business value by integrating Internet of Things architectures. Both architecture engineering and management of current information systems and business models are complex and currently integrating beside the Internet of Things synergistic subjects, like Enterprise Architecture in context with services & cloud computing, semantic-based decision support through ontologies and knowledge-based systems, big data management, as well as mobility and collaboration networks. To provide adequate decision support for complex business/IT environments, we have to make transparent the impact of business and IT changes over the integral landscape of affected architectural capabilities, like directly and transitively impacted IoT-objects, business categories, processes, applications, services, platforms and infrastructures. The paper describes a new metamodel-based approach for integrating Internet of Things architectural objects, which are semi-automatically federated into a holistic Digital Enterprise Architecture environment.

Interactive Functions of a Cockpit for Enterprise Architecture Planning

Analysis and planning of Enterprise Architectures (EA) is a complex task for stakeholders. The change of one architecture element has impact on multiple other elements because of manifold relationships and interactions between them. The interactive cockpit approach presented in this paper supports stakeholders planning and analyzing EAs and to tackle the intrinsic complexity. This approach supplies a cockpit with multiple viewpoints to put relevant information side-by-side without losing the context combined with interaction functionality. In this paper, we develop such cockpit starting with relevant use cases, describing a potential design based on well-established foundations in EA modeling, and outline an exemplary usage scenario.

Towards an integrated service-oriented reference enterprise architecture

New business information systems are integrating emerging cloud infrastructures with service-oriented platforms and intelligent user-centered mobile systems. Both architecture engineering and management of service-oriented enterprise architectures is complex and has to integrate synergistic disciplines like EAM - Enterprise Architecture and Management for Services & Cloud Computing, Semantic-based Decision Support through Ontologies and Knowledge-based Systems, Big Data Management, as well as Mobility and Collaboration Systems. It is necessary to identify affected decisions by runtime changes of a service-oriented runtime environment and architecture. We have to make transparent the impact of these changes over the integral landscape of affected EAM-capabilities, like directly and transitively impacted business categories, processes, applications, services, platforms and infrastructures. The paper describes a new Metamodel-based integration approach for Service-oriented Reference Enterprise Architectures.

Modeling Decisions for Collaborative Enterprise Architecture Engineering

New or adapted digital business models have huge impacts on Enterprise Architectures (EA) and require them to become more agile, flexible, and adaptable. All this changes are happening frequently and are currently not well documented. An EA consists of a lot of elements with manifold relationships between them. Thus changing the business model may have multiple impacts on other architectural elements. The EA engineering process deals with the development, change and optimization of architectural elements and their dependencies. Thus an EA provides a holistic view for both business and IT from the perspective of many stakeholders, which are involved in EA decision-making processes. Different stakeholders have specific concerns and are collaborating today in often-unclear decision-making processes. In our research we are investigating information from collaborative decision-making processes to support stakeholders in taking current decisions. In addition we provide all information necessary to understand how and why decisions were taken. We are collecting the decision-related information automatically to minimize manual time intensive work as much as possible. The core contribution of our research extends a decisional metamodel, which links basic decisions with architectural elements and extends them with an associated decisional case context. Our aim is to support a new integral method for multi-perspective and collaborative decision-making processes. We illustrate this by a practice-relevant decision-making scenario for Enterprise Architecture Engineering.

Social-Software-Based Support for Enterprise Architecture Management Processes

Modern enterprises reshape and transform continuously by a multitude of management processes with different perspectives. They range from business process management to IT service management and the management of the information systems. Enterprise Architecture (EA) Management seeks to provide such a perspective and to align the diverse management perspectives. Therefore, EA Management cannot rely on hierarchic - in a tayloristic manner designed - management processes to achieve and promote this alignment. It, conversely, has to apply bottom-up, information-centered coordination mechanisms to ensure that different management processes are aligned with each other and enterprise strategy. Social software provides such a bottom-up mechanism for providing support within EAM-processes. Consequently, challenges of EA management processes are investigated, and contributions of social software presented. A cockpit provides interactive functions and visualization methods to cope with this complexity and enable the practical use of social software in enterprise architecture management processes.

Architectural Decision Management for Digital Transformation of Products and Services

The digitization of our society changes the way we live, work, learn, communicate, and collaborate. The Internet of Things, Enterprise Social Networks, Adaptive Case Management, Mobility systems, A ...

Decision-Controlled Digitization Architecture for Internet of Things and Microservices

Digitization of societies changes the way we live, work, learn, communicate, and collaborate. In the age of digital transformation IT environments with a large number of rather small structures like Internet of Things (IoT), Microservices, or mobility systems are emerging to support flexible and agile digitized products and services. Adaptable ecosystems with service-oriented enterprise architectures are the foundation for self-optimizing, resilient run-time environments and distributed information systems. The resulting business disruptions affect almost all new information processes and systems in the context of digitization. Our aim are more flexible and agile transformations of both business and information technology domains with more flexible enterprise information systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates mechanisms for decision-controlled digitization architectures for Internet of Things and Microservices by evolving enterprise architecture reference models and state of the art elements for architectural engineering for micro-granular systems.

Multi-Perspective Decision Management for Digitization Architecture and Governance

The Internet of Things, Enterprise Social Networks, Adaptive Case Management, Mobility S ystems, Analytics for Big Data, and Cloudenvironments are emerging to support smart connected i.e. digital products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self- optimizing and resilient run-time environments for intelligent business services and related distributed information systems with service-oriented digitization architectures. We are investigatingmechanismsforflexibleadaptationandevolution of information systems with digital architecture in the context of the ongoing digital transformation. Our aim is to support flexibility and agile transformation for both business and related information systems through adaptation and dynamical evolution of their digital architectures. The present research paper investigates mechanisms of decision analytics for digitization architectures, putting a spotlight to Internet of Things architectures, by extending original enterprise architecture reference models with digitization architectures andtheirmulti- perspective architectural decision management.

Multi-perspective Digitization Architecture for the Internet of Things

Social networks, smart portable devices, Internet of Things (IoT) on base of technologies like analytics for big data and cloud services are emerging to support flexible connected products and agile services as the new wave of digital transformation. Biological metaphors of living and adaptable ecosystems with service-oriented enterprise architectures provide the foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems. We are extending Enterprise Architecture (EA) with mechanisms for flexible adaptation and evolution of information systems having distributed IoT and other micro-granular digital architecture to support next digitization products, services, and processes. Our aim is to support flexibility and agile transformation for both IT and business capabilities through adaptive digital enterprise architectures. The present research paper investigates additionally decision mechanisms in the context of multi-perspective explorations of enterprise services and Internet of Things architectures by extending original enterprise architecture reference models with state of art elements for architectural engineering and digitization.

Leveraging Analytics for Digital Transformation of Enterprise Services and Architectures

The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. The digitization of software-intensive products and services is enabled basically by four megatrends: Cloud Computing, Big Data Mobile Systems, and Social Technologies. This disruptive change interacts with all information processes and systems that are important business enablers for the current digital transformation. The Internet of Things, Social Collaboration Systems for Adaptive Case Management, Mobility Systems and Services for Big Data in Cloud Services environments are emerging to support intelligent user-centered and social community systems. Modern enterprises see themselves confronted with an ever growing design space to engineer business models of the future as well as their IT support, respectively. The decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures (EA), is duly needed. With the advent of intelligent user-centered and social community systems, the challenging decision processes can be supported in more flexible and intuitive ways. Tapping into these systems and techniques, the engineers and managers of the enterprise architecture become part of a viable enterprise, i.e. a resilient and continuously evolving system that develops innovative business models.