Over the years, a large amount of temporal data needs to be shared and exchanged on the Web. Resource Description Framework (RDF) has been widely accepted and has rapidly gained popularity to al RDF) model as mentioned in represent and share data in many application domains (e.g., the Data of Web, Linked Data, and Knowledge Graph). Accordingly, efficient management of temporal data based on RDF is of increasing importance. Much work has been devoted to the representation, querying, storage, and management of temporal RDF data. Therefore, to investigate and more importantly serve as helping researchers grasp the main ideas and results of temporal RDF data management, and to highlight an ongoing research on them, in this paper, we provide a full up-to-date overview of the current state of the art in temporal RDF data management, including representation, querying, storage, and other directions.

In detail, regarding to the representation of temporal RDF models, we first classify the existing temporal RDF models into two main categories according to their focuses (including the new RDF extension models and the original RDF models based on timestamp). We summarize and compare each model from the perspectives of syntax, semantics, and etc. Then, we further summarize the temporal RDF querying and storage techniques in detail. Moreover, to well introduce the main idea of each approach, we use some examples to explain each approach. In addition, the directions for future research and some comparisons and analyses are discussed in our whole survey. This survey will help readers understand and catch some key techniques about the issue and also identify some future research directions.

多年来，需要在Web上共享和交换大量的时间数据。正如在许多应用程序域中表示和共享数据（例如，Web数据，链接数据和知识图）中提到的那样，资源描述框架（RDF）已被广泛接受，并且已迅速普及到RDF模型。因此，基于RDF的时间数据的有效管理变得越来越重要。大量工作已投入到时间RDF数据的表示，查询，存储和管理中。因此，为了进行研究，更重要的是，它可以帮助研究人员掌握时态RDF数据管理的主要思想和成果，并着重强调正在进行的研究，在本文中，我们提供有关时间RDF数据管理的最新技术的完整概述，包括表示，查询，存储和其他方向。

详细地，关于时间RDF模型的表示，我们首先根据它们的关注点将现有的时间RDF模型分为两个主要类别（包括新的RDF扩展模型和基于时间戳的原始RDF模型）。我们从语法，语义等角度总结并比较了每个模型。然后，我们进一步详细总结了时态RDF查询和存储技术。此外，为了很好地介绍每种方法的主要思想，我们使用一些示例来解释每种方法。此外我们在整个调查中讨论了未来研究的方向以及一些比较和分析。这项调查将帮助读者理解和掌握有关该问题的一些关键技术，并确定一些未来的研究方向。