Data streams are becoming omnipresent on the Web. The Stream Reasoning (SR) paradigm, which combines Stream Processing with Semantic Web techniques, has been successful in processing these data streams. The progress in SR research has led to several applications in domains such as the Internet of Things, social media analysis, Smart Cities, and many others. Each of these applications produces and consumes data streams, however, there are no fixed guidelines on how to manage data streams on the Web, as there are for their static counterparts. More specifically, there is no fixed life cycle for Streaming Linked Data (SLD) yet. Tommasini et al. (2020) introduced an initial proposal for a SLD life cycle, however, it has not been verified if the proposed life cycle captures existing applications and no guidelines were given for each step.

In this paper, we survey existing SR applications and identify if the life cycle proposed by Tommasini et al. fully captures the surveyed applications. Based on our analysis, we found that some of the steps needed reordering or being split up. This paper proposes an update of the life cycle and surveys the existing literature for each life cycle step while proposing a number of guidelines and best practices. Compared to the initial proposal by Tommasini et al., we drill down into the details of the processing step which was previously neglected. The updated life cycle and guidelines serves as a blueprint for future SR applications. A life cycle for SLD that allows to efficiently manage data streams on the web, brings us a step closer to the realization of the SR vision.

数据流在 Web 上变得无所不在。将流处理与语义 Web 技术相结合的流推理 (SR) 范例已经成功地处理了这些数据流。SR 研究的进展已经在物联网、社交媒体分析、智慧城市等领域产生了多种应用。这些应用程序中的每一个都产生和使用数据流，但是，没有关于如何在 Web 上管理数据流的固定指南，就像它们的静态对应物一样。更具体地说，流式关联数据 (SLD) 还没有固定的生命周期。托马西尼等人。(2020) 提出了一项初步提案然而，SLD 生命周期尚未验证所提议的生命周期是否包含现有应用程序，并且没有为每个步骤提供指南。

在本文中，我们调查了现有的 SR 应用程序，并确定了 Tommasini 等人提出的生命周期是否符合要求。完全捕获调查的应用程序。根据我们的分析，我们发现一些步骤需要重新排序或拆分。本文提议更新生命周期并调查每个生命周期步骤的现有文献，同时提出一些指南和最佳实践。与 Tommasini 等人的最初提议相比，我们深入研究了以前被忽略的处理步骤的细节。更新后的生命周期和指南可作为未来 SR 应用程序的蓝图。SLD 的生命周期允许有效地管理 Web 上的数据流，使我们更接近 SR 愿景的实现。