The Metaverse offers a second world beyond reality, where boundaries are
non-existent, and possibilities are endless through engagement and immersive
experiences using the virtual reality (VR) technology. Many disciplines can
benefit from the advancement of the Metaverse when accurately developed,
including the fields of technology, gaming, education, art, and culture.
Nevertheless, developing the Metaverse environment to its full potential is an
ambiguous task that needs proper guidance and directions. Existing surveys on
the Metaverse focus only on a specific aspect and discipline of the Metaverse
and lack a holistic view of the entire process. To this end, a more holistic,
multi-disciplinary, in-depth, and academic and industry-oriented review is
required to provide a thorough study of the Metaverse development pipeline. To
address these issues, we present in this survey a novel multi-layered pipeline
ecosystem composed of (1) the Metaverse computing, networking, communications
and hardware infrastructure, (2) environment digitization, and (3) user
interactions. For every layer, we discuss the components that detail the steps
of its development. Also, for each of these components, we examine the impact
of a set of enabling technologies and empowering domains (e.g., Artificial
Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on
its advancement. In addition, we explain the importance of these technologies
to support decentralization, interoperability, user experiences, interactions,
and monetization. Our presented study highlights the existing challenges for
each component, followed by research directions and potential solutions. To the
best of our knowledge, this survey is the most comprehensive and allows users,
scholars, and entrepreneurs to get an in-depth understanding of the Metaverse
ecosystem to find their opportunities and potentials for contribution.

该文档介绍了多层次开发管道，包含计算、网络、通信和硬件基础设施，然后详细阐述了其中每个组件的发展细节以及相关技术对其进展的影响。最后概括性地介绍了该环境所面临的挑战和未来的研究方向，可为用户、学者和企业家提供全面的 Metaverse 生态系统的理解，以发现他们的机遇和潜力。

元宇宙：调查、趋势、新型管道生态系统和未来展望

The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future  Directions

In the recent years, machine learning has made great advancements that have
been at the root of many breakthroughs in different application domains.
However, it is still an open issue how make them applicable to high-stakes or
safety-critical application domains, as they can often be brittle and
unreliable. In this paper, we argue that requirements definition and
satisfaction can go a long way to make machine learning models even more
fitting to the real world, especially in critical domains. To this end, we
present two problems in which (i) requirements arise naturally, (ii) machine
learning models are or can be fruitfully deployed, and (iii) neglecting the
requirements can have dramatic consequences. We show how the requirements
specification can be fruitfully integrated into the standard machine learning
development pipeline, proposing a novel pyramid development process in which
requirements definition may impact all the subsequent phases in the pipeline,
and viceversa.

本文介绍了一种金字塔式的开发流程，将需求规范纳入标准的机器学习开发流程，以适应高风险或安全关键应用领域，并防止不考虑要求可能带来的严重后果。