Introduction
What is SciGraphs?
A set of nodes and edges encodes pairwise relationships, which makes graphs useful for spatial proximity, information flow, temporal evolution or hierarchical containment. Whether the model earns its keep usually comes down to whether a human can see structure in it: communities, bottlenecks, symmetries, anomalies.
Most network visualization still defaults to 2D node-link diagrams, with the failure modes those have at scale: edge crossings, overplotting, and hairballs that hide the topology of anything large or dense. Spatial networks, multi-layer urban contexts and geometrically constrained graphs also benefit from depth cues, lighting and a physically meaningful environment, which leaves a gap between analytical exploration and 3D scientific communication.
SciGraphs is an open-source Blender extension that closes that gap by putting graph ingestion, analysis and rendering in one pipeline. Analytical metadata survives the whole way through, alongside cinematographic composition, physically based lighting and realistic camera effects.
The two domains
| Domain | Description | Typical inputs |
|---|---|---|
| Combinatorial graphs | Spatialization derived from layout algorithms; analysis focuses on network measures and mesoscale structure. | Edge lists, GEXF, GraphML, SQL queries, SuiteSparse matrices |
| Spatial / geometric graphs | Geospatial networks and coordinate-faithful embeddings from external data sources. | OSMnx street networks, Overture Maps, sparse-matrix coordinates, urban morphology |
Why Blender?
Blender is a free, open-source 3D creation suite with three properties that matter here:
- A fully scriptable Python API that exposes every part of the application, from scene construction to render dispatch.
- Two production-grade render engines, Cycles (unbiased path tracer) and EEVEE Next (real-time rasterizer).
- Geometry Nodes, a node-based environment for procedural geometry that operates on named attributes.
That attribute model maps directly onto graph analytics. Metrics computed by SciGraphs are stored as per-node or per-edge named attributes, and Geometry Nodes read them to drive instance scale, color-ramp lookups, node size or any other visual parameter, leaving the source data untouched. Because Geometry Nodes evaluate lazily on the GPU and use hardware instancing, one modifier can place millions of glyphs and edge primitives with little memory overhead.
- The Guide covers concepts, installation, the system architecture, the sidebar interface, and the end-to-end pipeline.
- The Panel Reference documents every panel and subpanel in the sidebar, with a usage guide for each.
- The Tutorials are step-by-step walkthroughs of each individual panel, using the Burjassot and La Paz cases.
- The Examples are end-to-end walkthroughs of complete scenarios.