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Auflistung nach Schlagwort "Process Models"

1 - 3 von 3
  • Zeitschriftenartikel
    Agilität bei der Einführung von IT-Servicemanagement: Lösung klassischer Herausforderungen mit agilen Methoden
    (HMD Praxis der Wirtschaftsinformatik: Vol. 56, No. 2, 2019) Pröhl, Thorsten; Zarnekow, Rüdiger
    IT-Servicemanagement (ITSM) stellt für Unternehmen nach wie vor ein relevantes Thema dar, welches sowohl IT-Manager als auch CIOs von mittelständischen und Großunternehmen im Hinblick auf verschiedenartige Fragestellungen, wie ITSM-Einführung, Zertifizierung, Automatisierung, stärkere Kundenorientierung, Einsatz von KI oder Big Data Analyseverfahren, beschäftigt. Gerade bei der ITSM-Einführung oder Zertifizierung nutzen viele Unternehmen bisher klassische Vorgehensmodelle und sehen sich dabei regelmäßig mit unterschiedlichen Herausforderungen, wie Praxisorientierung von Prozessen, Widerstand gegen Änderung, singuläres Schnittstellenwissen, Zeitdruck oder fehlende Managementattention, konfrontiert. Die klassischen Modelle folgen dabei wasserfallartigen Ansätzen, welche bereits aus der Softwareentwicklung mit allen Vor- und Nachteilen bekannt sind. Die Nutzung agiler Techniken und Methoden kann die klassischen Herausforderungen bei der ITSM-Einführung adressieren und ermöglicht dabei zeitgleich die Geschwindigkeit und den Nutzen der Einführung zu erhöhen. IT Service Management (ITSM) continues to be a relevant topic for companies. Especially for both IT managers and CIOs of mid-sized and large enterprises who put emphasis on various issues, such as ITSM implementation, certification, automation, stronger customer focus, use of AI, or big data analysis methods. In fact, in the case of ITSM implementation or certification, many companies are currently using classic process models and are regularly confronted with various challenges involving practical orientation of processes, resistance to change, singular interface knowledge, time pressure or lack of management attention. Moreover, the classic models follow waterfall-like approaches, whose advantages and disadvantages are already known from software development. However, the use of agile techniques and methods can address the classical challenges of ITSM implementation, while at the same time increasing the speed and benefits of its adoption.
  • Zeitschriftenartikel
    A qualitative study of Machine Learning practices and engineering challenges in Earth Observation
    (it - Information Technology: Vol. 63, No. 4, 2021) Jentzsch, Sophie; Hochgeschwender, Nico
    A qualitative study of Machine Learning practices and engineering challenges in Earth ObservationMachine Learning (ML) is ubiquitously on the advance. Like many domains, Earth Observation (EO) also increasingly relies on ML applications, where ML methods are applied to process vast amounts of heterogeneous and continuous data streams to answer socially and environmentally relevant questions. However, developing such ML- based EO systems remains challenging: Development processes and employed workflows are often barely structured and poorly reported. The application of ML methods and techniques is considered to be opaque and the lack of transparency is contradictory to the responsible development of ML-based EO applications. To improve this situation a better understanding of the current practices and engineering-related challenges in developing ML-based EO applications is required. In this paper, we report observations from an exploratory study where five experts shared their view on ML engineering in semi-structured interviews. We analysed these interviews with coding techniques as often applied in the domain of empirical software engineering. The interviews provide informative insights into the practical development of ML applications and reveal several engineering challenges. In addition, interviewees participated in a novel workflow sketching task, which provided a tangible reflection of implicit processes. Overall, the results confirm a gap between theoretical conceptions and real practices in ML development even though workflows were sketched abstractly as textbook-like. The results pave the way for a large-scale investigation on requirements for ML engineering in EO.
  • Konferenzbeitrag
    A Vision Towards Generated Assistive Systems for Supporting Human Interactions in Production
    (Modellierung 2022 Satellite Events, 2022) Michael, Judith
    Human workers need to cope with complex production settings when handling and monitoring cyber-physical production systems. Assistive systems can provide situational step-by-step support for human behavior, e.g., when interacting with a machine or for manual assembly. These systems need to take personal knowledge, workers skills or personal restrictions into account and are therefore subject to privacy concerns. However, the engineering of such interactive assistive systems within the production domain is a complex task as they might support critical functionality in dangerous environments and have a high need for safety and privacy considerations due to processing personal data. We want to investigate how the software engineering process of assistive systems in production can be improved to achieve higher reusability. Current research focuses on specific use cases and implements systems specifically for those needs without reusability in mind. We suggest using behavior and context models in a generative approach, to create a reusable method to engineer assistive systems for production environments, either as own applications or as services integrated within digital twins. We have already applied model-driven methods for assistive systems in the smart home domain and discuss the opportunities and challenges of an application of these methods for the production domain. These methods can facilitate the engineering of assistive functionalities within applications in production while meeting privacy, adaptability, and context-sensitivity requirements.