知识图谱是一个交互式、众包的人类知识依赖关系图,将课程及其先修课程映射为节点和边。

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NOASSERTION

最近更新

2026-07-25

AI 仓库情报摘要
FR-AI / ANALYSIS

为什么值得关注

它通过先修链的拓扑深度和完成状态可视化课程之间的关系,帮助学习者规划学习路径并探索知识结构。

适合谁使用

  • 自学者
  • 教育工作者和课程设计者
  • 对知识映射感兴趣的开源贡献者
  • 探索跨学科路径的学生

典型使用场景

  • 通过先修链探索个性化学习序列
  • 发现任何课程的相关主题和推荐学习资源
  • 为特定学科贡献新课程数据以扩展图谱
  • 使用内置验证脚本确保数据完整性后再提交拉取请求

项目优势

  • 交互式可视化,带有颜色编码的完成状态和可展开的课程卡片
  • 众包数据模型,使用纯文本文件便于贡献
  • 自动验证(重复ID、循环依赖、悬空先修课程)集成在CI中
  • 双重许可:代码使用MIT,数据使用CC BY-SA 4.0

使用前须知

  • 数据质量依赖社区贡献,可能不完整或有偏差
  • 目前仅收录已添加的课程,许多学科缺失
  • 没有内置的用户认证或进度追踪功能,完成状态需手动标记

README 快速开始

✧ Atlas of Knowledge

An interactive dependency graph of human knowledge. Each node is a course (a subject you can learn); edges are prerequisites. Nodes are arranged into horizontal levels by topological depth (how deep in the prerequisite chain a subject sits), colored by your completion status, and expand on click to show a description, prerequisites, the topics covered, and curated learning resources.

Every course card carries a description, a full topic list, and references split into recommended / supplementary and tagged by type. See CONTRIBUTING.md for the data format.

https://ethanvieira.github.io/atlas-of-knowledge/

Contributing

The atlas is meant to be crowd-sourced — every course and resource lives in a plain data file under js/data/ (a lightweight node in the field file, plus a per-course detail file under js/data/details/), so anyone can add to a discipline they know. See CONTRIBUTING.md for the schema and workflow. Before opening a PR, run the validator:

node scripts/validate.js

It checks the whole catalog for duplicate ids, dangling prerequisites, dependency cycles and malformed entries — and the same check runs in CI on every pull request.

License

  • Code (the site's HTML/CSS/JS and tooling) — MIT.
  • Course data (everything under js/data/: courses, descriptions, topics, prerequisites and resource lists) — CC BY-SA 4.0.

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