Earth observation (EO) systems play a significant role in environmental monitoring and the prediction of natural disasters. These systems generate a massive amount of heterogeneous data stored in different formats. The exploitation of this data is still limited while, in most cases, data are not linked, and sources are not interoperable. Hence, data cannot be exploited as an interoperable global knowledge graph to have more in-depth analyzes of environmental phenomena. Ontology, as a knowledge representation formalism, is a promising solution for the semantic interoperability between this data. In this work, we present a modular ontology for environmental monitoring developed based on an original agile methodology. The so-called MEMOn (Modular Environmental Monitoring Ontology) aims to support semantic interoperability, data integration, and linking of heterogeneous data collected through a variety of observation techniques and systems. We also present real use case studies to show the usefulness of the proposed ontology.

地球观测（EO）系统在环境监测和自然灾害的预测中发挥着重要作用。这些系统生成大量以不同格式存储的异构数据。在大多数情况下，数据未链接且源不可互操作时，对这种数据的利用仍然受到限制。因此，不能将数据用作可互操作的全局知识图来对环境现象进行更深入的分析。本体作为一种知识表示形式，是一种有希望的解决方案，用于解决这些数据之间的语义互操作性。在这项工作中，我们提出了一种基于原始敏捷方法论开发的用于环境监控的模块化本体。所谓的MEMOn（模块化环境监控本体）旨在支持语义互操作性，数据集成，以及通过各种观察技术和系统收集的异构数据的链接。我们还提供了实际的用例研究，以显示提出的本体的有用性。