Informatik
Refine
Document Type
- Conference proceeding (59)
- Journal article (9)
- Book chapter (6)
Is part of the Bibliography
- yes (74)
Institute
- Informatik (74)
Publisher
- Springer (35)
- IEEE (8)
- Gesellschaft für Informatik e.V (7)
- Association for Information Systems (4)
- RWTH Aachen (4)
- University of Hawaii at Manoa (4)
- Elsevier (3)
- IGI Global (2)
- SciTePress (2)
- University of Hawai'i at Manoa (2)
The Internet of Things (IoT) fundamentally influences today’s 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 the Internet of Things into their evolving Enterprise Architecture Management environments. Both architecture engineering and management of current enterprise architectures is complex and has to integrate beside the Internet of Things synergistic disciplines like EAM - Enterprise Architecture and Management with disciplines like: 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, it is necessary to identify affected changes of Internet of Things environments and their related fast adapting architecture. We have to make transparent the impact of these changes over the integral landscape of affected EAM-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 partial Internet of Things objects, which are semi-automatically federated into a holistic Enterprise Architecture Management environment.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This defines the strategical context for composing resilient enterprise architectures for micro-granular digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of system architectures defines the moving context for adaptable systems, which are essential to enable the digital transformation. Enterprises are presently transforming their strategy and culture together with their processes and information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Since years a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things or mobile systems. In this paper, we are focusing on the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like Internet of Things and Microservices, as part of a new digital enterprise architecture. To integrate micro-granular architecture models to living architectural model versions we are extending more traditional enterprise architecture reference models with state of art elements for agile architectural engineering to support the digitalization of services with related products, and their processes.
The digital transformation of our life changes the way we work, learn, communicate, and collaborate. Enterprises are presently transforming their strategy, culture, processes, and their information systems to become digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things, Microservices and mobile services. Since years a lot of new business opportunities appear using the potential of services computing, Internet of Things, mobile systems, big data with analytics, cloud computing, collaboration networks, and decision support. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self optimizing and resilient run-time environments for intelligent business services and adaptable distributed information systems with service oriented enterprise architectures. This has a strong impact for architecting digital services and products following both a value-oriented and a service perspective. The change from a closed world modeling world to a more flexible open-world composition and evolution of enterprise architectures defines the moving context for adaptable and high distributed systems, which are essential to enable the digital transformation. The present research paper investigates the evolution of Enterprise Architecture considering new defined value-oriented mappings between digital strategies, digital business models and an improved digital enterprise architecture.
Intelligent systems and services are the strategic targets of many current digitalization efforts and part of massive digital transformations based on digital technologies with artificial intelligence. Digital platform architectures and ecosystems provide an essential base for intelligent digital systems. The paper raises an important question: Which development paths are induced by current innovations in the field of artificial intelligence and digitalization for enterprise architectures? Digitalization disrupts existing enterprises, technologies, and economies and promotes the architecture of cognitive and open intelligent environments. This has a strong impact on new opportunities for value creation and the development of intelligent digital systems and services. Digital technologies such as artificial intelligence, the Internet of Things, service computing, cloud computing, blockchains, big data with analysis, mobile systems, and social business network systems are essential drivers of digitalization. We investigate the development of intelligent digital systems supported by a suitable digital enterprise architecture. We present methodological advances and an evolutionary path for architectures with an integral service and value perspective to enable intelligent systems and services that effectively combine digital strategies and digital architectures with artificial intelligence.
Today, many companies are adapting their strategy, business models, products, services as well as business processes and information systems in order to expand their digitalization level through intelligent systems and services. The paper raises an important question: What are cognitive co-creation mechanisms for extending digital services and architectures to readjust the usage value of smart services? Typically, extensions of digital services and products and their architectures are manual design tasks that are complex and require specialized, rare experts. The current publication explores the basic idea of extending specific digital artifacts, such as intelligent service architectures, through mechanisms of cognitive co-creation to enable a rapid evolutionary path and better integration of humans and intelligent systems. We explore the development of intelligent service architectures through a combined, iterative, and permanent task of co-creation between humans and intelligent systems as part of a new concept of cognitively adapted smart services. In this paper, we present components of a new platform for the joint co-creation of cognitive services for an ecosystem of intelligent services that enables the adaptation of digital services and architectures.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the digital transformation since years. 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. They will shape future trends of business innovation and the next wave of information and communication technology. 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 enterprise architectures. The present research investigates mechanisms for flexible adaptation and evolution of digital enterprise architectures in the context of integrated synergistic disciplines like distributed service-oriented architectures and information systems, EAM - Enterprise Architecture and Management, metamodeling, semantic echnologies, web services, cloud computing and Big Data technology. Our aim is to support flexibility and agile transformations for both business domains and related enterprise systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems.
New business opportunities appeared using the potential of the Internet and related digital technologies, like the Internet of Things, services computing, artificial intelligence, cloud, edge, and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber-physical systems. Companies are transforming their strategy and product base, as well as their culture, processes and information systems to adopt digital transformation or to approach for digital leadership. Digitalization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. Digitalization has a substantial impact for architecting the open and complex world of highly distributed digital servcies and products, as part of a new digital enterprise architecture, which structure and direct service-dominant digital products and services. The present research paper investigates mechanisms for supporting the evolution of digital enterprise architectures with user-friendly methods and instruments of interaction, visualization, and intelligent decision management during the exploration of multiple and interconnected perspectives by an architecture management cockpit.
Digitization is the use of digital technologies for creating innovative digital business models and transforming existing business models, processes and systems. Digitization creates profound changes in the economy and society. Information is often captured and processed without human intervention using digital means. Digitization impacts nearly all products and services as well as the customer and the value-creation perspective.
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.
Leveraging textual information for improving decision making in the business process lifecycle
(2015)
Business process implementations fail, because requirements are elicited incompletely. At the same time, a huge amount of unstructured data is not used for decision-making during the business process lifecycle. Data from questionnaires and interviews is collected but not exploited because the effort doing so is too high. Therefore, this paper shows how to leverage textual information for improving decision making in the business process lifecycle. To do so, text mining is used for analyzing questionnaires and interviews.
Digital technologies are main strategic drivers for digitalization and offer ubiquitous data availability, unlimited connectivity, and massive processing power for a fundamentally changing business. This leads to the development and application of intelligent digital systems. The current state of research and practice of architecting digital systems and services lacks a solid methodological foundation that fully accommodates all requirements linked to efficient and effective development of digital systems in organizations. Research presented in this paper addresses the question, how management of complexity in digital systems and architectures can be supported from a methodological perspective. In this context, the current focus is on a better understanding of the causes of increased complexity and requirements to methodological support. For this purpose, we take an enterprise architecture perspective, i.e. how the introduction of digital systems affects the complexity of EA. Two industrial case studies and a systematic literature analysis result in the proposal of an extended Digital Enterprise Architecture Cube as framework for future methodical support.
Platforms feature increasingly complex architectures with regard to interconnecting with other digital platforms as well as with a variety of devices and services. This development also impacts the structure of digital platform ecosystems and forces providers of these services, devices, and services to incorporate this complexity in their decision-making. To contribute to the existing body of knowledge on measuring ecosystem complexity, the present research proposes two key artefacts based on ecosystem intelligence: On the one hand, complementarity graphs represent ecosystems with an ecosystem's functional modules as vertices and complementarities as edges. The nodes carry information about the category membership of the module. On the other hand, a process is suggested that can collect important information for ecosystem intelligence using proxies and web scraping. Our approach allows replacing data, which today is largely unavailable due to competitive reasons. We demonstrated the use of the artefacts in category-oriented complementarity maps that aggregate the information from complementarity graphs and support decision-making. They show which combination of module categories creates strong and weak complementarities. The paper evaluates complementarity maps and the data collection process by creating category-oriented complementarity graphs on the Alexa skill ecosystem and concludes with a call to pursue more research based on functional ecosystem intelligence.
The internet of things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud environments are emerging to support smart connected i.e. digital products and services and the digital transformation. Biological metaphors for living and adaptable ecosystems are currently providing the logical foundation for resilient run-time environments with serviceoriented digitization architectures and for self-optimizing intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution of information systems with digital architecture in the context of the ongoing digital transformation. The goal is to support flexible and agile transformations 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 micro-granular architectures, by extending original enterprise architecture reference models with digitization architectures and their multi-perspective architectural decision management.
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.
Enterprises are transforming their strategy, culture, processes, and their information systems to enlarge their digitalization efforts or to approach for digital leadership. The digital transformation profoundly disrupts existing enterprises and economies. In current times, a lot of new business opportunities appeared using the potential of the Internet and related digital technologies: The Internet of Things, services computing, cloud computing, artificial intelligence, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, microservices, or other micro-granular elements. Architecting micro-granular structures have a substantial impact on architecting digital services and products. The change from a closed-world modeling perspective to more flexible Open World of living software and system architectures defines the context for flexible and evolutionary software approaches, which are essential to enable the digital transformation. In this paper, we are revealing multiple perspectives of digital enterprise architecture and decisions to effectively support value and service oriented software systems for intelligent digital services and products.
Digitalization of products and services commonly causes substantial changes in business models, operations, organization structures and IT infrastructures of enterprises. Motivated by experiences and observations from digitalization projects, the paper investigates the effects of digitalization on enterprise architectures (EA). EA models serve as representation of business, information system and technical aspects of an enterprise to support management and development. By comparing EA models before and after digitalization, the paper analyzes the kinds of changes visible in the EA model. The most important finding is that newly created digitized products and the associated (product)- and enterprise architecture are no longer properly integrated into the overall architecture and even exist in parallel. Thus, the focus of this work is on showing these parallel architectures and proposing derivations for a better integration.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change drive current and next information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology with more flexible enterprise information systems through adaptation and evolution of digital architectures. The present research paper investigates the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like microservices and the Internet of Things, as part of a new composed digital architecture. To integrate micro-granular architecture models into living architectural model versions we are extending enterprise architecture reference models by state of art elements for agile architectural engineering to support digital products, services, and processes.
An enormous amount of data in the context of business processes is stored as images. They contain valuable information for business process management. Up to now this data had to be integrated manually into the business process. By advances of capturing it is possible to extract information from an increasing number of images. Therefore, we systematically investigate the potentials of Image Mining for business process management by a literature research and an in-depth analysis of the business process lifecycle. As a first step to evaluate our research, we developed a prototype for recovering process model information from drawings using Rapidminer.
Potentials of smart contracts-based disintermediation in additive manufacturing supply chains
(2019)
We investigate which potentials are created by using smart contracts for disintermediation in supply chains for additive manufacturing. Using a qualitative, critical realist research approach, we analyzed three case studies with companies active in additive manufactures. Based on interviews with experts from these companies, we could identify eight key requirements for disintermediation and associate four potentials of smart contracts-based disintermediation.