Two-tier demo seed dataset (Layer A public / Layer B private)

Esta página aún no está disponible en tu idioma.

Context

Artist Alley needs a realistic, studio-shaped dataset to (a) dogfood federation across two peers, (b) seed local dev + CI, (c) populate the hosted demo once it exists, and (d) produce marketing + README screenshots that show a populated DAM rather than an empty install.

The tension: the most compelling screenshots use rich, recognizable media, but anything shown publicly (README, marketing site, hosted demo, public CI artifacts) must be license-clean — we are publicly displaying every asset in frame. Mixing “attractive but IP-encumbered” content with “safe to publish” content in one dataset makes it impossible to know which surfaces can go public.

Decision

The seed dataset is two tiers, both curated under datasets/artist_alley/ (mounted on the self-hosted runner; a curated subset is copied locally for screenshot work):

Layer A — `site_a` (PUBLIC-SAFE)

“Artist Alley — Demo Studio Seed (Layer A)” — composed entirely of open-source, public-domain, and Creative Commons content. No IP-referenced or personal content.
Aggregate license: CC-BY-SA 4.0 (forced by the most restrictive included source — the Wikimedia gameplay videos are CC-BY-SA; combined with CC0/CC-BY/PD content the aggregate is CC-BY-SA).
Ships MANIFEST.json, dataset-metadata.json, and a canonical ATTRIBUTIONS.md listing every source + license. Sources include Kenney.nl (CC0 asset packs), Khronos glTF Sample Models (CC-BY/CC0), Wikimedia gameplay videos (CC-BY-SA), and other CC/PD material.
Format coverage spans every asset type the app supports — images, 3D (GLB/OBJ/FBX), audio (OGG/WAV), video (WEBM), documents (EPUB), fonts (TTF), vectors (SVG), HDR — so a seeded instance exercises the full viewer range.
This is the ONLY tier used for anything public: marketing-site screenshots, the OSS README screenshots, the hosted demo, and any public CI fixture. It is federation peer “site A” in the dogfood loop.

Layer B — `site_b` (PRIVATE)

May carry IP-referenced, personal, or otherwise not-publicly- redistributable content that makes for richer internal testing.
Never published. Dogfood peer “site B” + local testing only. No screenshots from Layer B reach the README, the marketing site, or the public demo.

Attribution obligation

CC-BY-SA 4.0 requires attribution + share-alike. Whenever Layer A content (or a screenshot containing it) is redistributed publicly, the ATTRIBUTIONS.md credit list must be preserved / linked. Practically: the marketing site + README screenshot sections carry a “Demo content: CC-BY-SA — see attributions” credit line pointing at the dataset’s attribution list.

Consequences

Positive:

A single, unambiguous rule for “can this go public”: Layer A only. No per-asset licensing audit at screenshot time.
Screenshots + hosted demo look genuinely rich (full format coverage) while staying license-clean.
The dogfood loop’s two peers (site_a / site_b) map cleanly onto the public/private split.

Negative:

Layer A excludes the most recognizable IP, so screenshots skew toward generic-but-clean studio content (Kenney kits, sample 3D models). That is the correct trade for publishability.
The attribution credit line is a standing obligation on every public surface that shows Layer A media.

Alternatives considered

Single mixed dataset with per-asset license flags. Rejected — a per-asset audit at every publish point is error-prone; one leaked IP-encumbered thumbnail in a README is a real problem.
Fully synthetic / AI-generated demo content we own outright. Considered as a future option; the curated CC/PD dataset ships now and carries real format diversity a generator would have to reproduce.

Reference

ADR 0049 — Encrypted federation + dogfood (the two-peer loop site_a / site_b feed)
ADR 0034 — Capability add-ons (heavy media the dataset exercises)
datasets/artist_alley/site_a/{MANIFEST.json, dataset-metadata.json, ATTRIBUTIONS.md} — the canonical dataset provenance