Use of Model-Driven Architecture in the storage of PM 2.5 and public health data
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Introduction: This paper addresses the storage of data on health events and PM2.5 particles in the city of Medellín, Colombia. The consolidation of data from heterogeneous sources poses a significant challenge in this context.
Objective: The aim of this study is to propose a metamodel that facilitates the integration and storage of these data using a model-based approach.
Methods: A modeled approach was developed to identify common aspects for building a data warehouse. An abstraction layer was defined over the conceptual models of particulate matter and health events.
Results: The main result was the creation of a data warehouse prototype that allows for the efficient consolidation of data on PM2.5 and health events. This prototype demonstrates the effectiveness of the proposed approach in data integration.
Conclusion: It is concluded that using a model-based approach strengthens decision-making in public health policies and quality management strategies in the healthcare sector.
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Accepted 2024-07-22
Published 2024-09-12
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