Cloud computing with its key facets and its inherent advantages still faces several challenges in the Internet of Things (IoT) ecosystem. The distance among the IoT end devices and cloud computing might be a problem for latency-sensitive applications such as catastrophe management and content transference applications. Fog computing is a novel paradigm to address such issues that playacts a significant role in massive and real-time data management systems in an IoT environment. Particularly IoT data management by fog computing is one important phase for latency reduction in latency-sensitive applications and necessary to generate more skilled knowledge and intelligent decisions. In this study, we used the SLR (systematic literature review) method to survey fog data management to understand the various topics and main contexts in this domain that have been newly offered. The target of this article is classifying and analyzing the researches about the fog data management domain which has been released from 2014 to 2019. A context-based taxonomy is offered for fog data management including data processing, data storage and data security based on the context of papers that are elected with the SLR method in our study. Based on presented technical taxonomy, the grouped papers in any context are compared with each other pursuant to some metrics of fog data management reference model. Then, for any selected research, the new findings, advantages, and weaknesses are debated. Finally, based on studies the open issues in fog data management and their related challenges for future researches are highlighted.

具有关键方面及其固有优势的云计算在物联网（IoT）生态系统中仍面临数项挑战。物联网终端设备与云计算之间的距离可能是对延迟敏感的应用程序（例如灾难管理和内容传输应用程序）的一个问题。雾计算是解决此类问题的新颖范式，它在物联网环境中的大规模实时数据管理系统中扮演着重要角色。特别是通过雾计算进行物联网数据管理是减少对延迟敏感的应用程序中延迟的一个重要阶段，并且对于生成更多熟练的知识和智能决策是必不可少的。在这个研究中，我们使用SLR（系统文献综述）方法来调查雾数据管理，以了解该领域中新提供的各种主题和主要环境。本文的目标是对2014年至2019年发布的雾数据管理领域的研究进行分类和分析。为雾数据管理提供基于上下文的分类法，包括基于上下文的数据处理，数据存储和数据安全性在我们的研究中使用SLR方法选出的论文。根据提出的技术分类法，根据雾数据管理参考模型的某些度量标准，可以将在任何情况下分组的论文进行相互比较。然后，对于任何选定的研究，都会讨论新的发现，优点和缺点。最后，