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A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare

机译:用于支持特定领域的知识发现的元模型集成:医疗保健的案例研究

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摘要

Knowledge management is one of the key priorities of many organizations. They face different challenges in the implementation of knowledge management processes, including the transformation of tacit knowledge—experience, skills, insights, intuition, judgment and know-how—into explicit knowledge. Furthermore, the increasing number of information sources and services in some domains, such as healthcare, increase the amount of information available. Therefore, there is a need to transform that information in knowledge. In this context, learning ecosystems emerge as solutions to support knowledge management in a different context. On the other hand, the dashboards enable the generation of knowledge through the exploitation of the data provided from different sources. The model-driven development of these solutions is possible through two meta-models developed in previous works. Even though those meta-models solve several problems, the learning ecosystem meta-model has a lack of decision-making support. In this context, this work provides two main contributions to face this issue. First, the definition of a holistic meta-model to support decision-making processes in ecosystems focused on knowledge management, also called learning ecosystems. The second contribution of this work is an instantiation of the presented holistic meta-model in the healthcare domain.
机译:知识管理是许多组织的主要优先事项之一。他们在实施知识管理流程时面临着不同的挑战,包括改变默契的知识体验,技能,见解,直觉,判断和专业知识的改造。此外,在一些域中越来越多的信息来源和服务,例如医疗保健,增加可用信息量。因此,需要在知识中转换该信息。在这种情况下,学习生态系统出现为在不同背景下支持知识管理的解决方案。另一方面,仪表板通过利用不同来源提供的数据来实现知识。这些解决方案的模型驱动的开发是可以通过以前工作中开发的两个META模型进行的。即使这些元模型解决了几个问题,学习生态系统元模型也缺乏决策支持。在这种情况下,这项工作提供了两个主要贡献来面对这个问题。首先,整体元模型的定义,支持重点是知识管理的生态系统中的决策过程,也称为学习生态系统。这项工作的第二次贡献是医疗领域的呈现整体元模型的实例化。

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