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In digital knowledge systems, even seemingly immutable facts like mountain heights are dynamic data points vulnerable to obsolescence. The case of Australia's Mount Bartle Frere—where conflicting elevations (1,622m vs. 1,611m) persisted across Wikidata, Wikipedia, and Encyclopædia Britannica for years—exposes critical flaws in how we manage authoritative knowledge.

The Data Discrepancy Detective Work

When software engineer Andrew Jenkinson spotted inconsistent elevation data for Queensland's highest peak, he uncovered a digital archaeology project:
- Wikidata sourced its 1,622m claim from an uncited 2011 German Wikipedia entry
- English Wikipedia showed 1,622m in its infobox but 1,611m in article text after a 2016 survey
- Geoscience Australia quietly listed 1,611m with a 1993 timestamp

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The infamous xkcd comic captures the compulsion to correct online errors (CC BY-NC 2.5)

Jenkinson traced the 1,622m figure to a 2007 Queensland trail map, later disproven by a 2016 GPS survey using state-of-the-art equipment. The survey report ([IMAGE:3]) conclusively established 1,611.204m as the corrected elevation—yet this update failed to propagate through knowledge ecosystems.

Why Outdated Data Persists

Three systemic failures emerged:
1. Provenance Black Holes: Wikidata's German Wikipedia import lacked source verification, creating a "telephone game" of data
2. Update Fragmentation: Wikipedia's infobox/Wikidata sync created conflicting truths within single articles
3. Authority Ambiguity: Google's Knowledge Graph ([IMAGE:4]) still displays the outdated 1,622m height without source citations

Fixing the Knowledge Graph

Jenkinson's remediation strategy proved revealing:
1. Wikidata First: Updated elevation with survey evidence and deprecated old measurements
2. Wikipedia Sync: Deleted local infobox entry, letting it repopulate from corrected Wikidata
3. Stubborn Legacy: Official tourism sites (queensland.com) still show 1,622m years later

The Data Integrity Imperative

This case underscores urgent challenges for developers:
- Temporal Context: Knowledge graphs need "valid from/to" metadata for facts
- Provenance Chaining: Single-hop citations are insufficient; we need audit trails
- Update Propagation: Changing a fact in Wikidata doesn't purge it from downstream caches

As AI systems increasingly rely on these knowledge bases, the Mount Bartle Frere discrepancy illustrates how easily outdated data becomes embedded truth. The real summit we're climbing? Building systems where facts carry expiration dates and pedigree records—because in the digital landscape, mountains do move.