Automatic Code Generation of Data Visualization for Structural Health Monitoring



Structural health monitoring, model driven development, data visualization, domain specific languages


Structural Health Monitoring (SHM) aims at detecting, localizing, and characterizing damages in civil, mechanical, and aerospatial structures, which are hardly detectable in visual inspections. The collection, analysis, and visualization of data captured by sensors installed on these structures can be strongly supported by modern techniques of Data Science. In particular, the visualization of these data provides valuable help to experts on structural health and decision makers on preventive and corrective maintenance. Unfortunately, existing systems of data visualization still demand those stakeholders for a high level of software programming skills to take full advantage of visual and interactive exploration of data that sensors capture and output. This work introduces a model-driven approach to develop data visualization in the domain of structural health monitoring, in particular, of bridges. This approach is based on the definition of a Domain Specific Language (DSL) that describes the main concepts of an infrastructure of sensors typically used in SHM, along with common graphics and visual alternatives of data visualization. This DSL is instantiated by a modeling language, composed of a metamodel, a visual representation of concepts, and a set of model-to-text transformation rules. In this way, non-programmers can implement their own data visualization from a graphical and intuitive design, by automatically generating the corresponding code. This approach was implemented in a modeling and code-generation tool, called Vis4bridge, whose usability and output were successfully evaluated through the development of tasks and case studies.


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Author Biographies

Braulio Quiero Hernández, Universidad de Concepción, Chile

Braulio Quiero es Ingeniero Civil Informático de la Universidad Católica de la Santísima Concepción, Chile (2017) y Magíster en Ciencias de la Computación de la Universidad de Concepción, Chile (2021). Su trabajo se orienta a la generación automática de código, interfaces humano-computador, y visualización de datos.

Gonzalo Rojas, Universidad de Concepción, Chile

Gonzalo Rojas es Profesor Asistente del Departamento de IngenieríaInformática y Ciencias de la Computación de la Universidad de Concepción, Chile, y Doctor en Ingeniería de Software por la Universidad Politécnica deValencia, España (2008). Su trabajo se orienta a arquitectura de software, sistemas de Big Data, visualización de datos y calidad de software.


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How to Cite

Quiero Hernández, B., & Rojas, G. (2022). Automatic Code Generation of Data Visualization for Structural Health Monitoring. IEEE Latin America Transactions, 100(XXX). Retrieved from