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.
Highlights
The main difference between Model-driven development (MDD) and model-driven architecture (MDA) is that MDA determines a set of standards to develop the approach, such as meta-object facility (MOF), unified modeling language (UML), Extensible Markup
This work proposes an integration of two meta-models to deal with issues related to knowledge generation and knowledge discovery in learning ecosystems
A dashboard meta-model has been merged into a learning ecosystem meta-model to support decision-making processes related to the information flows and management objectives that are present within these ecosystems
Summary
Three main concepts are used to refer to these changes, information society, knowledge society, and digital society. These concepts are strictly related, and sometimes authors use them as synonyms. Each concept emphasizes an aspect of society. According to Dufva and Dufva [1], digital technologies are entangled in the structures of society in many different, complex and even contradictory ways. In this context, the concept of information society is used above all when dealing with technological aspects and their effects on economic growth and employment [2]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
