A space-air-ground-sea integrated network (SAGSIN) has emerged as a cornerstone of 6G systems, establishing a unified global architecture by integrating multi-domain network resources. Motivated by the demand for real-time situational awareness and intelligent operational maintenance, digital twin (DT) technology was initially regarded as a promising solution, owing to its capability to create virtual replicas and emulate physical system behaviors. However, in the context of SAGSIN, the high-fidelity, full-scale modeling paradigm inherent to conventional DTs encounters fundamental limitations, including prohibitive computational overhead, delayed model synchronization, and cross-system semantic gaps. To address these limitations, this survey paper proposes a novel twinning framework: goal-oriented semantic twin (GOST). Unlike DTs that pursue physical mirroring, GOST prioritizes ``utility'' over ``fidelity,'' leveraging semantic technologies and goal-oriented principles to construct lightweight, task-specific representations. This paper systematically articulates the GOST framework through three layers: knowledge-based semantics, data-driven semantics, and goal-oriented principles. Furthermore, we provide a comprehensive tutorial on constructing GOST by detailing its core enabling technologies and introduce a multidimensional evaluation framework for GOST. We present a case study targeting collaborative tracking tasks in remote satellite-UAV networks, demonstrating that GOST significantly outperforms conventional DTs in timeliness of perceptual data and collaborative tracking. Finally, we outline research directions, establishing GOST as a transformative twinning paradigm to guide the development of SAGSIN.

翻译：空天地海一体化网络（SAGSIN）作为6G系统的基石，通过整合多域网络资源构建了统一的全球架构。受实时态势感知与智能运维需求的驱动，数字孪生（DT）技术因其能够创建虚拟副本并模拟物理系统行为，最初被视为一种有前景的解决方案。然而，在SAGSIN场景下，传统DT所固有的高保真、全尺度建模范式面临根本性局限，包括计算开销过大、模型同步延迟以及跨系统语义鸿沟等。为解决这些局限，本综述论文提出了一种新型孪生框架：目标导向语义孪生（GOST）。与追求物理镜像的DT不同，GOST优先考虑“效用”而非“保真度”，利用语义技术与目标导向原则构建轻量级、任务特定的表征。本文通过三个层次系统阐述了GOST框架：基于知识的语义、数据驱动的语义以及目标导向原则。此外，我们通过详细阐述其核心使能技术，提供了构建GOST的综合性教程，并引入了针对GOST的多维评估框架。我们以远程卫星-无人机网络中的协同跟踪任务为案例研究，证明GOST在感知数据时效性与协同跟踪方面显著优于传统DT。最后，我们展望了未来研究方向，将GOST确立为一种变革性的孪生范式，以指导SAGSIN的发展。