Context: Data visualizations and dashboards are essential in disseminating information to broad audiences. However, designing these instruments is complex due to the multitude of involved factors. Theoretical framewor...
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Context: Data visualizations and dashboards are essential in disseminating information to broad audiences. However, designing these instruments is complex due to the multitude of involved factors. Theoretical frameworks are therefore critical to guide the design and implementation of data visualizations. Objective: This article presents the approach used to pinpoint key features that impact the creation of information visualizations, organize these features using meta-modelling, and validate the final artefact through expert judgement. Method: meta-modelling facilitates the distillation of characteristics and functionalities critical for the development of information systems. Utilizing this method, a dashboard meta-model was constructed in preceding research, yielding a framework of abstract components and connections to delineate specific products. This meta-model serves as a robust tool for the automated generation of information visualizations and dashboards. Nonetheless, to confirm its quality and efficacy, it underwent a thorough quality assessment and expert evaluation to identify and address potential shortcomings. Results: The validation process resulted in positive ratings and constructive feedback to enhance the meta-model's present iteration. Experts mainly highlighted the meta-model's complexity and the clarity of certain entities, noting potential confusion for non-experts. Conclusions: While the meta-model is confirmed to be a coherent and pertinent tool, it requires additional clarifications to simplify its complexity. Addressing this, graphical interfaces have been developed to enable users to interact with the dashboard meta-model-and to create dashboard instances-through straightforward interactions.
The intensive use of models in model-driven engineering (MDE) raises the need to develop meta-models with different aims, such as the construction of textual and visual modelling languages and the specification of sou...
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The intensive use of models in model-driven engineering (MDE) raises the need to develop meta-models with different aims, such as the construction of textual and visual modelling languages and the specification of source and target ends of model-to-model transformations. While domain experts have the knowledge about the concepts of the domain, they usually lack the skills to build meta-models. Moreover, meta-models typically need to be tailored according to their future usage and specific implementation platform, which demands knowledge available only to engineers with great expertise in specific MDE platforms. These issues hinder a wider adoption of MDE both by domain experts and software engineers. In order to alleviate this situation, we propose an interactive, iterative approach to meta-model construction, enabling the specification of example model fragments by domain experts, with the possibility of using informal drawing tools like Dia or yED. These fragments can be annotated with hints about the intention or needs for certain elements. A meta-model is then automatically induced, which can be refactored in an interactive way, and then compiled into an implementation meta-model using profiles and patterns for different platforms and purposes. Our approach includes the use of a virtual assistant, which provides suggestions for improving the meta-model based on well-known refactorings, and a validation mode, enabling the validation of the meta-model by means of examples.
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