📢 New paper at SIBGRAPI 2026!

📢 New paper at SIBGRAPI 2026!

We're happy to share "Reveal: A Provenance-Aware System for Multimodal Urban Data Exploration," presented at SIBGRAPI 2026.

Reveal is a visual analytics system that tackles:

🔎 Multimodal text and image search over a shared CLIP embedding space

🧩 Set operations to combine and refine urban concepts

🗺️ Linked views: embedding plots, image galleries, word clouds, and spatial heatmaps

🧭 An exploration diagram that captures analytical provenance, making each analysis transparent, reproducible, and reusable

In case studies with an urban planner, Reveal helped expand the Project Sidewalk accessibility taxonomy with 11 new fine-grained categories, covering more than 1,600 newly labeled images.

We then reused the captured provenance as a "semantic blueprint" to replicate the analysis on Chicago street-level imagery.

This work continues our research line on provenance and scientific data management, applied here to urban visual analytics. It is a collaboration between the UFFeScience Research Group (Daniel de Oliveira, Aline Paes, and Marcos Lage), UIC (Leonardo Ferreira and Fabio Miranda), FGV (Joao Rulff), and UC Berkeley (Maryam Hosseini), and it builds on Leonardo Ferreira's master's work.

Congratulations to all co-authors!

💻 Code and tutorial: https://lnkd.in/dGzXh5V9

#SIBGRAPI2026 #eScience #UFF #Provenance #VisualAnalytics #UrbanComputing #MultimodalData