The large volume and variety of data produced in the current Big Data era lead companies to seek solutions for the efficient data management. Within this context, NoSQL databases rise as a better alternative to the traditional relational databases, mainly in terms of scalability and availability of data. A usual feature of NoSQL databases is to be schemaless, i.e., they do not impose a schema or have a flexible schema. This is interesting for systems that deal with complex data, such as GIS. However, the lack of a schema becomes a problem when applications need to perform processes such as data validation, data integration, or data interoperability, as there is no pattern for schema representation in NoSQL databases. On the other hand, the JSON language stands out as a standard for representing and exchanging data in document NoSQL databases, and JSON Schema is a schema representation language for JSON documents that it is also leading to become a standard. However, it does not include spatial data types. From this limitation, this paper proposes an extension to JSON Schema, called JS4Geo, that allows the definition of schemas for geographic data. We demonstrate that JS4Geo is able to represent schemas of any NoSQL data model, as well as other standards for geographic data, like GML and KML. We also present a case study that shows how a data integration system can benefit of JS4Geo to define local schemas for geographic datasets and generate an integrated global schema.

当前大数据时代产生的海量数据和种类繁多，促使公司寻求有效的数据管理解决方案。在这种情况下，主要在可伸缩性和数据可用性方面，NoSQL数据库作为传统关系数据库的更好替代品而兴起。NoSQL数据库的通常特征是无模式的，即，它们不强加模式或具有灵活的模式。对于处理复杂数据的系统（例如GIS）而言，这很有趣。但是，当应用程序需要执行诸如数据验证，数据集成或数据互操作性之类的过程时，缺少架构便成为问题，因为NoSQL数据库中没有用于模式表示的模式。另一方面，JSON该语言是用于表示和交换文档NoSQL数据库中的数据的标准，而JSON Schema是JSON文档的模式表示语言，它也正逐渐成为一种标准。但是，它不包括空间数据类型。由于这个限制，本文提出了对JSON模式的扩展，称为JS4Geo，它允许定义地理数据的模式。我们证明JS4Geo能够表示任何NoSQL数据模型的架构，以及其他地理数据标准，例如GML和KML。我们还提供了一个案例研究，展示了数据集成系统如何使JS4Geo受益，以为地理数据集定义本地架构并生成集成的全局架构。