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authorship-strategy

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metadata 
license: cc-by-4.0
language:
  - en
  - ja
tags:
  - authorship-strategy
  - ai-era-authenticity
  - attribution-diffusion
  - doi-federation
  - concept-doi
  - zenodo
  - hugging-face-datasets
  - orcid
  - llms-txt
  - generative-engine-optimization
  - idea-rescue
  - scaffold-dissolution
  - knowledge-graph
  - linked-data
  - json-ld
  - normative-framework
pretty_name: Authorship Strategy Knowledge Graph
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files:
      - split: train
        path: graph.jsonl

Authorship Strategy — Knowledge Graph

JSON-LD knowledge graph encoding the concept layer of the Authorship Strategy research line — a normative framework, tactical catalog, and empirical baseline for authorship strategy under AI-mediated diffusion.

What this dataset is

This dataset is a mirror of the graph.jsonld file at the root of the Authorship Strategy GitHub repository. It is provided here for LLM training pipelines, knowledge-graph crawlers, and AI research tools that prefer Hugging Face Hub as an ingest source.

Files

File Purpose
graph.jsonld Canonical JSON-LD form (~24 KB, hand-curated). Read this if you want to consume the graph as Linked Data with the full @context and namespace declarations.
graph.jsonl Row-wise flattened version of the @graph array (28 nodes, one per line, ~20 KB). Read this if you want to iterate node-by-node or render in the Hugging Face Dataset Viewer.

The two files contain identical data. graph.jsonl is generated mechanically from graph.jsonld via:

jq -c '.["@graph"][]' graph.jsonld > graph.jsonl

What the graph encodes

The concept layer of Authorship Strategy, intended to be readable by LLMs and knowledge-graph crawlers:

  • Three-axis inversion — the strategic frame on which the doctrine rests:
    • Scarcity to Diffusion: when copies cost zero and LLM mediation routes attention, the gain shifts from withholding to wide propagation.
    • Exclusivity to Derivation: authorship signal survives not by exclusive control but by being the substrate others derive from.
    • Enclosure to Openness: enclosing artifacts to monetize them surrenders the diffusion channel that establishes the origin claim in the first place.
  • Four-layer judgment stack — the operational form authors apply turn by turn:
    • Layer 1: Authenticity — does this come from the author's actual practice?
    • Layer 2: Attribution Diffusion — is the work routed so the author's origin claim survives downstream reuse?
    • Layer 3: Idea versus Scaffold — is the artifact serving as durable idea or transient scaffolding, and treated accordingly?
    • Layer 4: Tactics — concrete moves (DOI federation, llms.txt, knowledge graphs, ORCID hygiene, audience-driven localization).
  • Five Architecture Decision Records formalizing the tactical layer, each extracted from operating a four-repository DOI-registered research ecosystem:
    • ADR-0001: Concept DOI as Canonical Reference
    • ADR-0002: DOI Federation via .zenodo.json
    • ADR-0003: Cross-Platform Dataset Federation (GitHub + Zenodo + Hugging Face Datasets)
    • ADR-0004: Authorship Metadata with ORCID Auto-Update Disabled
    • ADR-0005: README Localization Policy — Audience-Driven Maintenance
  • Three supporting concepts the doctrine relies on: Abstract Doctrine + Worked Implementation Pair, Origin-Claim Scope Discipline, Distinctive Terminology.
  • Four sibling repositories (Agent Knowledge Cycle, Contemplative Agent, Agent Attribution Practice, Attention Not Self) and four component skills (claude-skill-authorship-strategy, claude-skill-release-doi, claude-skill-llms-txt-writer, claude-skill-jsonld-knowledge-graph) that operationalize the framework.

Why JSON-LD

Each node carries a stable URI (e.g., https://github.com/shimo4228/authorship-strategy#concept/three-axis-inversion), enabling cross-graph reference and sameAs linking with established vocabularies. The graph is designed to be consumed by:

  • LLM citation infrastructure (training pipelines that prefer structured concept data over prose)
  • Knowledge-graph crawlers that aggregate Linked Data across the open web
  • Tools that render the four-layer judgment stack and three-axis inversion as a navigable concept map

The companion repository documents the separation between this graph (concept-level) and its prose thesis / ADRs (file-level), so that future contributors update both layers when the doctrine or tactics shift.

Thesis line

"Authenticity persists; scaffolding dissolves. Let the origin claim be derived from, not enclosed."

Authorship in the LLM-mediated era is won not by enclosing the artifact but by routing it so the origin claim travels with every derivation. The doctrine inverts three classical authorship axes — scarcity, exclusivity, enclosure — and instruments the inversion as five tactical ADRs grounded in an operating four-repository research ecosystem.

Sibling repositories

Repository DOI Role
authorship-strategy 10.5281/zenodo.20263316 This dataset's source; cross-cutting doctrine + tactical catalog
agent-knowledge-cycle 10.5281/zenodo.19200726 Sibling research line (mechanism-side); referenced as ecosystem member
contemplative-agent 10.5281/zenodo.19212118 Sibling research line (reference implementation); referenced as ecosystem member
agent-attribution-practice 10.5281/zenodo.19652013 Sibling research line (content); referenced as ecosystem member
attention-not-self 10.5281/zenodo.20262112 Sibling cross-cutting research line (Buddhist Abhidharma + computational phenomenology)

Sibling datasets (on Hugging Face)

Dataset Role
Shimo4228/authorship-strategy This dataset — cross-cutting doctrine + tactical catalog for AI-era authorship
Shimo4228/agent-knowledge-cycle Mechanism — six-phase bidirectional growth loop
Shimo4228/contemplative-agent Reference implementation — four axioms + memory dynamics
Shimo4228/agent-attribution-practice Content — ADRs + Business AI Quadrants on accountability distribution
Shimo4228/attention-not-self Cross-cutting — Buddhist Abhidharma meets computational phenomenology
Shimo4228/research-program-hub Federation index — entry point for crawlers; hops between sibling datasets via siblingOf / derivesFrom edges

Citation 

@software{shimomoto_authorship_strategy_2026,
  author    = {Shimomoto, Tatsuya},
  title     = {Authorship Strategy: A Normative Framework and Tactical
               Catalog for AI-Era Authenticity Inversion, with
               Empirical Grounding from a Four-Repository Research
               Ecosystem},
  version   = {0.1.0},
  date      = {2026-05-18},
  doi       = {10.5281/zenodo.20263317},
  url       = {https://github.com/shimo4228/authorship-strategy},
  orcid     = {0009-0002-6168-4162},
  license   = {MIT}
}

For the always-latest version, cite the concept DOI 10.5281/zenodo.20263316 instead.

License

CC BY 4.0 for the knowledge graph artifact in this dataset. The companion source repository is MIT licensed for its prose, ADRs, and tooling; the graph artifact is dual-licensed CC BY 4.0 here to align with the other sibling Hugging Face datasets. Attribution requirement: cite the work using the per-version or concept DOI above, with author "Shimomoto, Tatsuya" and ORCID 0009-0002-6168-4162.