Points of interest in visual context.
Technology & Mission
We use Self-Organizing Maps (SOM) to learn and observe the representation of high-dimensional datasets that are challenging to visualize otherwise — revealing data topology to put complex observations in visual context.
"Bianor builds upon Lilypond, the visualization tool we developed to create enhanced Self-Organizing Map (SOM) displays. Lilypond was inspired by water lilies; as you can see, the extracted maps look like clusters of lily pads floating on the water's surface. Following this metaphor, Bianor is more like a scenery of descending butterflies, where we can observe which historical pattern they land on and whether it seems out of context." — Mate Balogh, Lead at Bianor, Ophelia R&D
Applications
Discover how Bianor is being used to explore high-dimensional data.
Bringing Interactivity to the Lilypond Library
Bianor relies on the Lilypond library to obtain data representations. We demonstrated how the features of Bianor elevate how we interact with the created maps across manifold learning, supervised and unsupervised analysis, and anomaly contextualization.
Turning Products into a Visual Landscape
Bianor was used to visualize a catalog of LEGO® sets to help discovering models that are similar to the reference product. Instead of endless pagination and plain comparison tables, customers explore the map of products, while being informed about store availability and price, and being one click away from purchase.
Get Started
Recommended for individual researchers, data scientists, and curious minds seeking a lightweight, zero-cloud setup directly on their local machine.
-
Clone the
ophelia-rnd/bianorrepository and run it -
Train an
SomRepresentationmodel on the desired dataset and save it via MLflow -
Link your representation through the
catalog.yamlfile - Use the Bianor application to interactively inspect your data's two-dimensional representation
Our Ecosystem: Foundation & Frontier
From exploratory data analysis to automated contextual insights.
Community Edition
High-dimensional observations mapped to visual contexts in 2D.
-
SomRepresentationmodels tracked in MLflow -
Interactive visualizer with various layers and
options
powered bylilypond - Open-source
- Full local setup is supported
- Deployable as a Databricks application
Designed for data scientists, researchers — and curious minds.
Biome Edition
Advanced platform for hierarchical views and context extraction.
- All Community features
- Advanced interactive features
- Hierarchical view of representations and projections
- Instant and detailed contextualization
Designed for advanced workflows and custom requirements.