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Knowledge Management Process for Air Quality Systems based on Data Warehouse Specification

机译:基于数据仓库规范的空气质量系统知识管理流程

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Even though several systems for Air Quality (AQ) monitoring have been in existence for over a decade, a research model for Knowledge Management (KM) of AQ data has to be created in order to enhance the decision-making and organize the air quality data collected from the Internet of Things (IoT) consumer devices. This model should be made more performant by ensuring greater flexibility and interoperability between devices and emerging technologies. In this context, we propose an approach for representing Data WareHouse (DWH) schema based on an ontology that captures the multidimensional knowledge of tools, techniques, and technologies used for novel AQ systems. This enhances decision-making by coping with potential problems such as data sources heterogeneity and covering the various phases of the decision-making life cycle.
机译:尽管有几十年的空气质量(AQ)监测的几个系统,但必须创建一个AQ数据的知识管理(KM)的研究模型,以增强决策并组织空气质量数据 从东西互联网(物联网)消费者设备收集。 通过确保设备和新兴技术之间的更大的灵活性和互操作性,应更加表现该模型。 在此上下文中,我们提出了一种基于本体论代表数据仓库(DWH)模式的方法,该内容捕获用于新型AQ系统的工具,技术和技术的多维知识。 这通过应对潜在的问题来提高决策,例如数据源异质性,并覆盖决策生命周期的各个阶段。

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