The growing trends in automation, Internet of Things, big data and cloud computing technologies have led to the fourth industrial revolution (Industry 4.0), where it is possible to visualize and identify patterns and insights, which results in a better understanding of the data and can improve the manufacturing process. However, many times, the task of data exploration results difficult for manufacturing experts because they might be interested in analyzing also data that does not appear in pre-designed visualizations and therefore they must be assisted by Information Technology experts.

In this paper, we present a proposal materialized in a semantic-based visual query system developed for a real Industry 4.0 scenario that allows domain experts to explore and visualize data in a friendly way. The main novelty of the system is the combined use that it makes of captured data that are semantically annotated first, and a 2D customized digital representation of a machine that is also linked with semantic descriptions. Those descriptions are expressed using terms of an ontology, where, among others, the sensors that are used to capture indicators about the performance of a machine that belongs to a Industry 4.0 scenario have been modeled. Moreover, this semantic description allows to: formulate queries at a higher level of abstraction, provide customized graphical visualizations of the results based on the format and nature of the data, and download enriched data enabling further types of analysis.

自动化，物联网，大数据和云计算技术的增长趋势导致了第四次工业革命（工业4.0），在这里可以可视化并识别模式和见解，从而更好地理解数据和可以改善制造过程。但是，很多时候，制造专家很难进行数据探索，因为他们可能也有兴趣分析未在预先设计的可视化中出现的数据，因此必须由信息技术专家协助。

在本文中，我们提出了在针对实际工业4.0场景开发的基于语义的视觉查询系统中实现的提案，该领域允许领域专家以友好的方式探索和可视化数据。该系统的主要创新之处在于，它结合了捕获的数据（首先进行语义注释）和机器的2D定制数字表示（也与语义描述相关联）的组合使用。这些描述是使用本体的术语表达的，其中，用于捕获属于工业4.0场景的机器性能指标的传感器已建模。而且，这种语义描述允许：在更高的抽象层次上制定查询，基于数据的格式和性质提供定制的图形化可视化结果，