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References: Learning Graph Quality, Validation, and File Formats

  1. Directed Acyclic Graph - Wikipedia - Explains the mathematical definition and properties of DAGs, including why cycles cannot exist and how topological structure is verified, grounding this chapter's cycle-detection and self-dependency checks.

  2. Directed Graph - Wikipedia - Defines indegree and outdegree formally as the counts of head-end and tail-end edges at a vertex, the exact vocabulary this chapter uses to classify foundational and goal concepts.

  3. JSON - Wikipedia - Describes the JSON data-interchange format's syntax, history, and design goals, supporting this chapter's coverage of the nodes/edges structure used to store a validated learning graph.

  4. Introduction to Algorithms (3rd Edition) - Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein - MIT Press - Its graph algorithms chapter presents the white/gray/black depth-first-search coloring scheme this chapter's cycle-detection code directly implements, plus formal treatment of connectivity and degree.

  5. Designing Data-Intensive Applications - Martin Kleppmann - O'Reilly Media - Covers data encoding and schema evolution across JSON, CSV, and other formats, directly relevant to this chapter's comparison of JSON, JSON Schema, CSV, YAML, and Markdown for storing a learning graph.

  6. Understanding JSON Schema - JSON Schema Official Documentation - A complete reference for JSON Schema keywords, types, and validation rules, expanding on this chapter's example of requiring an id and label on every learning graph node.

  7. YAML Specification 1.2.2 - YAML.org - The official, formal specification for YAML's indentation-based syntax, useful for understanding the mkdocs.yml and chapter-frontmatter files this chapter cites as YAML examples.

  8. Markdown Guide: Basic Syntax - Markdown Guide - A practical reference for Markdown's heading, list, and emphasis syntax, the publishing format this chapter identifies as the home for chapter prose and glossary entries.

  9. Directed Graphs (Algorithms, 4th Edition companion site) - Princeton University (Sedgewick & Wayne) - Presents working implementations of directed-cycle detection and topological sort, illustrating the same depth-first-search cycle-checking logic this chapter's Python example walks through.

  10. csv — CSV File Reading and Writing - Python Software Foundation - Official documentation for Python's csv module, supporting this chapter's CSV-to-JSON conversion script and its use of csv.DictReader to parse concept and dependency rows.