Modeling is one of the most important steps in developing a database. In traditional databases, the Entity Relationship (ER) and Unified Modeling Language (UML) models are widely used. But how are NoSQL databases being modeled? We performed a systematic mapping review to answer three research questions to identify and analyze the levels of representation, models used, and contexts where the modeling process occurred in the main categories of NoSQL databases. We found 54 primary studies where we identified that conceptual and logical levels received more attention than the physical level of representation. The UML, ER, and new notation based on ER and UML were adapted to model NoSQL databases, in the same way, formats such as JSON, XML, and XMI were used to generate schemas through the three levels of representation. New contexts such as benchmark, evaluations, migration, and schema generation were identified, as well as new features to be considered for modeling NoSQL databases, such as the number of records by entities, CRUD operations, and system requirements (availability, consistency, or scalability). Additionally, a coupling and co-citation analysis was carried out to identify relevant works and researchers.

中文翻译：

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数据建模和 NoSQL 数据库 - 系统映射回顾

建模是开发数据库的最重要步骤之一。在传统数据库中，实体关系 (ER)和统一建模语言 (UML)模型被广泛使用。但是如何对 NoSQL 数据库进行建模呢？我们进行了系统的映射审查以回答三个研究问题，以识别和分析 NoSQL 数据库主要类别中建模过程发生的表示级别、使用的模型和上下文。我们发现了 54 项主要研究，我们发现概念和逻辑层面比物理层面的表现更受关注。UML、ER 以及基于 ER 和 UML 的新符号被改编为 NoSQL 数据库建模，同样地，JSON、XML 和 XMI 等格式被用于通过三个表示级别生成模式。确定了基准、评估、迁移和模式生成等新环境，以及为 NoSQL 数据库建模需要考虑的新特性，例如实体的记录数量、CRUD 操作和系统要求（可用性、一致性或可伸缩性）。此外，还进行了耦合和共被引分析，以确定相关工作和研究人员。