---
id: "knowledge-graph-analytics"
date: "2026-04-07"
title: "From pretty graph to research workbench — analytics, paths, and Wikipedia for your knowledge graph"
summary: "The 3D knowledge graph now has an insights panel that ranks key entities, detects topic clusters, surfaces bridges, and lets you trace connections between any two entities — plus one-click Wikipedia lookup that opens articles right next to the graph."
image: "/medias/kg.jpg"
header: "Feature"
tags: [knowledge-graph, analytics, ux, wikipedia]
---

A knowledge graph with five thousand entities is impressive to look at and almost useless to read. You can rotate it, zoom it, watch the physics simulation settle, and still walk away with no sense of what's important. That changes today. The graph view has a new analytics layer that summarizes the network into actionable insights, plus an interactive path finder and one-click Wikipedia lookup on every entity.

## The Insights panel

A new sidebar opens from the toolbar with four cards:

- **Key Entities** — the most structurally important entities, ranked by how well-connected they are to other well-connected entities. This is different from raw mention counts: a famous physicist mentioned twice in passages full of other key entities can outrank a generic term mentioned hundreds of times.
- **Topics** — clusters of entities that frequently appear together. In an academic corpus these tend to map to research domains; in a history vault, to periods; in business documents, to product lines. Each topic is auto-labeled by its top entities (e.g. "Einstein & Relativity") and gets its own color.
- **Bridges** — entities that connect otherwise separate parts of the graph. These are often the most interesting nodes because they reveal non-obvious connections — an interdisciplinary scholar, a parent company that owns brands in different sectors, a concept that spans two fields.
- **Graph Health** — a traffic-light status (good / fair / poor) that flags fragmentation, isolated entities, and possible duplicates that the entity resolver missed.

Everything in the panel is clickable. Click an entity, the 3D view focuses on its neighborhood. Click a topic, the view filters down to just that cluster. Click a bridge, you jump straight to it.

## Find a connection between two entities

The new Path Finder answers the most human question: how is X related to Y? Pick two entities from autocomplete, click "Find connection", and the graph shows you the shortest chain of entities linking them — with the source documents that established each step.

If multiple equally short paths exist, you can expand "alternative paths" to see them all. Einstein might connect to the Nobel Prize through one collaborator and to the same prize through a different one. Both stories are visible, both come from your corpus.

## Re-encode the same graph, four ways

Two new toolbar dropdowns let you change what node size and color represent without rebuilding anything:

- **Size**: Mentions, Importance, Bridges, or Connectivity — the same graph reveals different stories depending on what you ask of it
- **Color**: Type or Topic — switch from ontological coloring (people, organizations, places) to topical coloring (the Louvain communities)

Switching modes preserves the layout. Only the visual encoding changes, so you can compare angles instantly.

## Wikipedia, in line

Click any node in the 3D view and two things happen at once: the graph focuses on the entity's neighborhood, and a Wikipedia panel opens in the top-left corner with matching articles, thumbnails, and short descriptions. Click an article and Daneel fetches the page, converts it to readable text, and renders it directly in the document viewer next to the graph. No new tab, no losing your place.

The disambiguation works in your favor. If your vault mentions "John Tate" and Wikipedia returns five different people, you can pick the right one (the mathematician, not the actor or the boxer) from the descriptions. Results are cached locally for a week to avoid hitting the API repeatedly.

## What this means for you

The graph view is no longer just a visualization. It's a set of structured questions you can ask about your corpus: who matters, what's grouped together, what bridges what, how is anything related to anything else, and what does the rest of the world know about each entity. All running in your browser, with the analytics layer wrapping a well-tested graph theory library and 99 unit tests covering the math.

Build a knowledge graph today, click around, and tell us what you find.

---

[Read on site](https://daneel.injen.io/news/knowledge-graph-analytics.html?utm_source=extension_news_reader&utm_medium=extension_settings&utm_campaign=extension)