Smart ecosystems are the drivers of modern society. They control infrastructures of socio-techno-economic importance, ensuring their stable and sustainable operation. Smart ecosystems are governed by digital twins -- real-time virtual representations of physical infrastructure. To support the open-ended and reactive traits of smart ecosystems, digital twins need to be able to evolve in reaction to changing conditions. However, digital twin evolution is challenged by the intertwined nature of physical and software components, and their individual evolution. As a consequence, software practitioners find a substantial body of knowledge on software evolution hard to apply in digital twin evolution scenarios and a lack of knowledge on the digital twin evolution itself. The aim of this paper, consequently, is to provide software practitioners with tangible leads toward understanding and managing the evolutionary concerns of digital twins. We use four distinct digital twin evolution scenarios, contextualized in a citizen energy community case to illustrate the usage of the 7R taxonomy of digital twin evolution. By that, we aim to bridge a significant gap in leveraging software engineering practices to develop robust smart ecosystems.

翻译：智能生态系统是现代社会的驱动力。它们控制着具有社会-技术-经济重要性的基础设施，确保其稳定和可持续运行。智能生态系统由数字孪生——物理基础设施的实时虚拟表征——所治理。为支持智能生态系统的开放性和反应性特质，数字孪生需要能够根据变化的条件进行演化。然而，数字孪生演化面临着物理组件与软件组件相互交织的特性及其各自演化的挑战。因此，软件从业者发现大量关于软件演化的知识难以应用于数字孪生演化场景，且数字孪生演化本身的知识存在缺失。因此，本文旨在为软件从业者提供理解和管理数字孪生演化问题的具体指引。我们通过公民能源社区案例中的四个不同数字孪生演化场景，阐释数字孪生演化的7R分类法的应用。藉此，我们致力于弥合在运用软件工程实践开发稳健智能生态系统方面存在的显著差距。