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

Sensors (Basel). 2020 Jul 22;20(15):4072. doi: 10.3390/s20154072.

Abstract

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.

Keywords: dashboard; health ecosystem; healthcare; knowledge management; meta-model; meta-model integration; model-driven development; technological ecosystem.

MeSH terms

  • Delivery of Health Care*
  • Knowledge Discovery*
  • Learning