# Knowledge Graph UI

DS254. Future / AI: Interaction Model. Page: https://ui.codeatlas.com.br/atlas/knowledge-graph-ui/. Index: https://ui.codeatlas.com.br/llms/atlas.txt

Shows relations between entities, evidence and processes.

- Status in 2026: Active. In current use.
- Trend 2027 to 2030: Rising in some contexts (an editorial projection, not a forecast).
- The term: Known technical term or standard.

## Traits

- graph
- clusters
- filters

Typical settings: Knowledge, Security, AI.

## When to use it, and when not

Consider it when the task and motivation match: researchers and relationship analysts. Typical settings: knowledge, security, ai.

Be careful when the risk below would hurt the main task: large graphs become unreadable.

Audience (a hypothesis about motivation and task, never measured, not a statement about any group): Researchers and relationship analysts.

## UX risk and how to reduce it

- Risk: Large graphs become unreadable.
- Mitigation and accessibility: Table summary and path search.
- How to check: Test with realistic scenarios: task success, accuracy, reversal, auditability, understanding of what the system does on its own, and a human's ability to step in.

## Evidence

Emerging: exploratory work, with no causal validation for this style.

The sources support the principles that apply to this term. None shows that this style works better or is preferred.

- [E06] Wagemans, Elder, Kubovy, Palmer, Peterson, Singh, von der Heydt (2012). A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure-ground organization. https://doi.org/10.1037/a0029333 (Established). Does not support: Any claim about interface styles. It is a review of perception, not of screens, and says nothing about preference.
- [E08] W3C Web Accessibility Initiative (2021). WCAG 2 supplemental guidance. https://www.w3.org/WAI/WCAG2/supplemental/ (Standard or guideline). Does not support: Normative requirements: supplemental guidance is advisory, not required for conformance. This page is an index; a specific recommendation needs the linked document.

## Limits

- The atlas is a broad, living catalogue, not every style that exists. No authority enumerates them, and the classes (movement, aesthetic, design system, layout, pattern, principle) overlap.
- The 1 to 5 scores are relative editorial judgements. They are not results of a study and not a measure of quality.
- An audience is a hypothesis about motivation, task and context. It was never measured and says nothing about any age, gender or other group.
- The sources support underlying principles (visual complexity, legibility, grouping, accessibility, platform conventions). None shows that a particular style works better or is preferred.
- The 2027 to 2030 trend is an editorial projection, not a forecast.
- Terms in the Future / AI category rest on exploratory work, some of it preprints, with no causal validation.

Last reviewed 2026-10-25.

## Heuristic scales

Relative editorial judgements from 1 to 5, not results of a study.

- Visual complexity: 5 / 5 (heuristic)
- Expressiveness: 3 / 5 (heuristic)
- Information density: 5 / 5 (heuristic)

## In our library

No design-style recipe implements this term yet; build it from `--ca-*` tokens.

## Prompt for your AI

```text
Design this interface in the "Knowledge Graph UI" direction (future / ai, interaction model): Shows relations between entities, evidence and processes.
Visual and interaction traits to use: graph, clusters, filters.
Main UX risk: Large graphs become unreadable. Mitigate it: Table summary and path search.
Keep it accessible to WCAG 2.2 AA: contrast, visible focus, keyboard operation, 24 px minimum targets, reflow at 320 CSS px and reduced motion.
Keep the content, hierarchy and behavior the same as a plain baseline so the two can be compared. Do not claim the style performs better; the choice should be validated with users.
```