ProVega: A Grammar to Ease the Prototyping, Creation, and Reproducibility of Progressive Data Analysis and Visualization Solutions
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866915909642223616 |
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| author | Filosa, Matteo Blasilli, Graziano Martino, Emilio Angelini, Marco |
| author_facet | Filosa, Matteo Blasilli, Graziano Martino, Emilio Angelini, Marco |
| contents | Modern data analysis requires speed for massive datasets. Progressive Data Analysis and Visualization (PDAV) emerged as a discipline to address this problem, providing fast response times while maintaining interactivity with controlled accuracy. Yet it remains difficult to implement and reproduce. To lower this barrier, we present ProVega, a Vega-Lite-based grammar that simplifies PDAV instrumentation for both simple visualizations and complex visual environments. Alongside it, we introduce Pro-Ex, an editor designed to streamline the creation and analysis of progressive solutions. We validated ProVega by reimplementing 11 exemplars from the literature-verified for fidelity by 39 users-and demonstrating its support for various progressive methods, including data-chunking, process-chunking, and mixed-chunking. An expert user study confirmed the efficacy of ProVega and the Pro-Ex environment in real-world tasks. ProVega, Pro-Ex, and all related materials are available at https://github.com/XAIber-lab/provega |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_02096 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | ProVega: A Grammar to Ease the Prototyping, Creation, and Reproducibility of Progressive Data Analysis and Visualization Solutions Filosa, Matteo Blasilli, Graziano Martino, Emilio Angelini, Marco Human-Computer Interaction Modern data analysis requires speed for massive datasets. Progressive Data Analysis and Visualization (PDAV) emerged as a discipline to address this problem, providing fast response times while maintaining interactivity with controlled accuracy. Yet it remains difficult to implement and reproduce. To lower this barrier, we present ProVega, a Vega-Lite-based grammar that simplifies PDAV instrumentation for both simple visualizations and complex visual environments. Alongside it, we introduce Pro-Ex, an editor designed to streamline the creation and analysis of progressive solutions. We validated ProVega by reimplementing 11 exemplars from the literature-verified for fidelity by 39 users-and demonstrating its support for various progressive methods, including data-chunking, process-chunking, and mixed-chunking. An expert user study confirmed the efficacy of ProVega and the Pro-Ex environment in real-world tasks. ProVega, Pro-Ex, and all related materials are available at https://github.com/XAIber-lab/provega |
| title | ProVega: A Grammar to Ease the Prototyping, Creation, and Reproducibility of Progressive Data Analysis and Visualization Solutions |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2604.02096 |