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oai:gredos.usal.es:10366/1691982026-01-23T01:03:20Zcom_10366_4386com_10366_4349com_10366_3946com_10366_3823col_10366_4387

MetaViz – A graphical meta-model instantiator for generating information dashboards and visualizations Vázquez Ingelmo, Andrea García Peñalvo, Francisco J. Therón Sánchez, Roberto Data visualization Information dashboards Meta-modeling Software product line Model-driven development [EN]This work presents the application of meta-modeling to the data visualization and dashboards’ domain to obtain two main products: a system that allows the instantiation of the meta-model through a graphical interface and a code generator that takes the instantiation of the meta-model as an input to generate visualizations and dashboards. Methods: A domain engineering approach complemented with an example-driven methodology was iter- atively employed to develop the dashboard meta-model. This meta-model was subsequently used as an input to implement a code generator of information dashboards. These two artifacts were finally com- bined to design and develop the architecture of MetaViz. Results: Through this process, it was possible to generate visualizations and dashboards using visual ele- ments and basic interactions. MetaViz allows the generation of basic charts (line charts, scatter plots, pie charts, etc.) as well as more complex displays with interactive behavior along different views, layouts, and operations. Conclusions: The development of MetaViz has served as proof of the viability and benefits of applying these methodologies to a complex domain, but also to set the foundations of a system that allows users to trace every single element from a data visualization to its most primitive values. 2026-01-22T12:53:30Z 2026-01-22T12:53:30Z 2022 info:eu-repo/semantics/article Andrea Vázquez-Ingelmo, Francisco José García-Peñalvo, Roberto Therón, MetaViz – A graphical meta-model instantiator for generating information dashboards and visualizations, Journal of King Saud University - Computer and Information Sciences, Volume 34, Issue 10, Part B, 2022, Pages 9977-9990, ISSN 1319-1578, https://doi.org/10.1016/j.jksuci.2022.09.015. (https://www.sciencedirect.com/science/article/pii/S1319157822003445) 1319-1578 http://hdl.handle.net/10366/169198 10.1016/j.jksuci.2022.09.015 eng https://doi.org/10.1016/j.jksuci.2022.09.015 http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional