Data Schematic: add visual cues denoting agent/machine/human produced/curated/verified data #4474

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1. jqnatividad

   changed the title [-]Data Schematic: add visual cues denoting agent/human produced data[/-] [+]Data Schematic: add visual cues denoting agent/machine/human produced/curated/verified data[/+] on Aug 21, 2026
2. jqnatividad commented on Aug 27, 2026

   

   jqnatividad

   on Aug 27, 2026

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   Investigation notes: current state & suggested shape

   What exists today

   Provenance in the Data Schematic is document-level only, never per-field:

   • x-qsv.generated_by — describegpt bakes a full attribution block into the schema (tool+version, command line, model, API URL, language, timestamp). viz renders it in three places: the dictionary drawer footer, the page footer, and the tour's meta panel (Model: line).
   • WARNING lines — describegpt appends per-prompt-type warnings ("Label and Description generated by an LLM… Verify before using!"). That's the closest thing to an "AI-generated" cue, and it's a blunt block of text, not a per-datum hint.
   • x-qsv.tour.generated_by — same convention on the tour envelope.

   Mapping the six categories onto current reality

   Category	Today
   1. Deterministic computed	Everything from the stats cache: chart geometry, types, cardinality, min/max, the self-inferred dictionary fallback. Implicitly computed — no marker.
   2. Deterministic + human-verified	No mechanism.
   3. AI-generated	describegpt's title / description / x-qsv.tags / content_type / tour narration. Only detectable by the presence of generated_by.
   4. AI + human-verified	No mechanism. A human editing an LLM dictionary leaves no trace (viz deliberately tolerates hand-edited sidecars and re-validates on read).
   5. AI + adversarial AI review	No mechanism. Closest is --two-pass DictionaryRefine, but that's same-model cross-field refinement, not adversarial review — and it re-emits as PromptType::Dictionary, erasing even that distinction.
   6. Human-generated	A hand-written dictionary — detectable only by the absence of a describegpt attribution block.

   Categories 2, 4, 5 need a new schema contract; 1, 3, 6 are inferable today from what's already stored.

   Suggested shape (two phases)

   Phase 1 — no schema change, inference only. viz can already classify coarsely: dictionary text with generated_by present ⇒ AI (✨-class badge); absent ⇒ human/unknown (👤); stats-derived facts and self-inferred labels ⇒ computed (⚙️). Render as a small badge + hover tooltip (title / aria-label) in the dictionary drawer rows, KPI tile corners, panel subtitles, and tour popovers, with a legend next to the existing attribution footer. This covers 3 of the 6 categories and establishes the visual language.

   Phase 2 — explicit x-qsv.provenance contract, per-property (and on the tour envelope), loosely aligned with W3C PROV vocabulary for portal interop (relevant to the CKAN/DCAT angle):

   "x-qsv": { "provenance": { "source": "ai", "verified": "human",
              "model": "gemma-3", "verified_at": "2026-08-27T…" } }

   • describegpt stamps source: "ai" on what it authors
   • a future --review-model (different model, adversarial prompt) could stamp verified: "ai"
   • human attestation via a hand edit or a small qsv schema helper

   This unlocks categories 2/4/5.

   Implementation considerations

   • Every badge label/tooltip needs curated i18n catalog keys in all supported locales.
   • Any tour/HTML template change requires regenerating the gallery pages.
   • KPI tile headers are contested real estate — viz: KPI tile doubles the aggregation prefix when the dictionary title already carries it ("Total Total Revenue") #4499 touches the same spot; coordinate the tile-corner badge with that fix.
   • The version-1 x-qsv.tour envelope pattern (Rust builds the envelope, LLM supplies prose only) is the right precedent for provenance — keep the machine-readable part out of the LLM's hands.

   🤖 Generated with Claude Code
3. jqnatividad commented on Sep 4, 2026

   

   jqnatividad

   on Sep 4, 2026

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   Also check DTPR for AI

   https://www.dtpr.ai/en
4. jqnatividad

   added

   enhancementNew feature or request. Once marked with this label, its in the backlog.New feature or request. Once marked with this label, its in the backlog.

   AI

   on Sep 13, 2026