A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare
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. Fur...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/15/4072 |
| _version_ | 1797561703575060480 |
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| author | Andrea Vázquez-Ingelmo Alicia García-Holgado Francisco José García-Peñalvo Roberto Therón |
| author_facet | Andrea Vázquez-Ingelmo Alicia García-Holgado Francisco José García-Peñalvo Roberto Therón |
| author_sort | Andrea Vázquez-Ingelmo |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T18:17:36Z |
| format | Article |
| id | doaj.art-16efedf23d8548cebaf818541e269440 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T18:17:36Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-16efedf23d8548cebaf818541e2694402023-11-20T07:31:39ZengMDPI AGSensors1424-82202020-07-012015407210.3390/s20154072A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in HealthcareAndrea Vázquez-Ingelmo0Alicia García-Holgado1Francisco José García-Peñalvo2Roberto Therón3GRIAL Research Group, Computer Science Department, University of Salamanca, 37008 Salamanca, SpainGRIAL Research Group, Computer Science Department, University of Salamanca, 37008 Salamanca, SpainGRIAL Research Group, Computer Science Department, University of Salamanca, 37008 Salamanca, SpainVisUSAL, GRIAL Research Group, Computer Science Department, University of Salamanca, 37008 Salamanca, SpainKnowledge 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.https://www.mdpi.com/1424-8220/20/15/4072model-driven developmentdashboardmeta-modelknowledge managementhealthcaretechnological ecosystem |
| spellingShingle | Andrea Vázquez-Ingelmo Alicia García-Holgado Francisco José García-Peñalvo Roberto Therón A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare Sensors model-driven development dashboard meta-model knowledge management healthcare technological ecosystem |
| title | A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare |
| title_full | A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare |
| title_fullStr | A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare |
| title_full_unstemmed | A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare |
| title_short | A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare |
| title_sort | meta model integration for supporting knowledge discovery in specific domains a case study in healthcare |
| topic | model-driven development dashboard meta-model knowledge management healthcare technological ecosystem |
| url | https://www.mdpi.com/1424-8220/20/15/4072 |
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