Towards Model-Driven Dashboard Generation for Systems-of-Systems
Maria Teresa Rossi, Alessandro Tundo, Leonardo Mariani
TL;DR
The paper tackles the challenge of configuring dashboards for large-scale Systems-of-Systems where KPIs proliferate and dashboards must evolve. It proposes a model-driven, technology-agnostic workflow that converts a simple KPI list into an abstract dashboard model and then into target dashboard implementations. The approach enables non-experts to generate useful visualizations automatically and lets experts adjust dashboards by editing the abstract model rather than GUI operations. By decoupling KPI definition from dashboard technology and providing Grafana-specific translation, it promises reusable, scalable dashboard generation across platforms.
Abstract
Configuring and evolving dashboards in complex and large-scale Systems-of-Systems (SoS) can be an expensive and cumbersome task due to the many Key Performance Indicators (KPIs) that are usually collected and have to be arranged in a number of visualizations. Unfortunately, setting up dashboards is still a largely manual and error-prone task requiring extensive human intervention. This short paper describes emerging results about the definition of a model-driven technology-agnostic approach that can automatically transform a simple list of KPIs into a dashboard model, and then translate the model into an actual dashboard for a target dashboard technology. Dashboard customization can be efficiently obtained by solely modifying the abstract model representation, freeing operators from expensive interactions with actual dashboards.