audiala/audiala-places

Audiala Places — Curated Multilingual Travel POIs

33,289 travel points of interest across 93 countries, each with a Wikidata QID, WGS84 coordinates, names in 11 languages, a type/category slug, fame signals (Wikidata PageRank + sitelink count), a link to a published travel guide on audiala.com in each of the 11 languages, and an ML target: search_impressions_decile, how visible each place's guides are in Google Search.

The curation filter is editorial: a place is included if and only if Audiala has published a full travel guide for it. This dataset is deliberately not exhaustive — it is a quality-bar dataset, not an "every POI in the world" dump.

Dataset structure

One row per Wikidata entity. Provided as CSV (flat columns) and GeoJSON (FeatureCollection of Point features with the same properties).

Field	Type	Description
wikidata_id	string	Wikidata QID, primary key
name_en … name_ru	string	Name in en, fr, de, es, pt, it, hi, zh, cs, ja, ru (native script; English fallback for the ~0.2 % without a translation)
latitude, longitude	float	WGS84 decimal degrees
country_iso2	string	ISO 3166-1 alpha-2
country_en	string	English country name
city_en	string	English city name
category	string	One of 50 type slugs (castle, museum, church, bridge, square, …), derived from Wikidata P31/P279* with name-pattern fallback
article_tier	string	structured (rich guide format) or legacy
wikidata_pagerank	float	Wikidata PageRank (danker all-wiki run); empty for ~17 % of rows
sitelinks	int	Count of Wikimedia project pages linked to the entity
url_en … url_ru	string	Canonical audiala.com guide URL per language (native-script paths for hi/zh/ja/ru)
search_impressions_decile	int	ML target. Google Web impressions of the place's guide pages (11 languages summed, 2026-07-03 → 2026-09-25) as a relative decile: 0 = none (177 rows), 1 lowest … 10 highest (~3,311 rows each)

ML task: predict search visibility

Given open facts about a travel place, predict how often its guide pages appear in Google Search. The target mixes real search demand with how well Audiala's pages rank, so it measures search visibility, not a place's global popularity. It is ordinal: use Spearman or quadratic weighted kappa, and hold out whole cities or countries to test generalization.

Baseline (gradient-boosted trees on sitelinks, PageRank, category, country, coordinates, article tier and number of language URLs; 5-fold CV): Spearman 0.49, exact decile 13.6 % (chance ≈ 9 %), within ±1 40.6 %. Sitelinks alone reach Spearman 0.45. The multilingual names and geography are largely untapped. Raw impressions, clicks, CTR and positions are not published.

Intended uses

• Tabular ML benchmark: predict search_impressions_decile from open features.
• Ranking / recommending travel destinations (fame signals included).
• Multilingual POI name lookup keyed by Wikidata QID.
• Map layers of curated (guide-backed) attractions.
• Joining editorial travel content to Wikidata/OSM entities.

Limitations

• Not exhaustive. Coverage = Audiala's published-guide catalog; skewed toward the US, Western Europe, and India, clustered around ~1,360 cities. Absence means "no guide yet", not "not notable".
• Category is best-effort (~87 % Wikidata-typed, rest heuristic; building and attraction are weak classes).
• A small long tail of QID mis-mappings may remain (207 detectable ones were removed at build time). Reports welcome.
• Guide URLs were 100 % live (HTTP 200) on a 300-URL random sample at build time (2026-09-28); retired pages return 410.
• The search target covers one summer window (2026-07-03 → 2026-09-25), so seasonal places are skewed.
• Fame signals are snapshots and drift as Wikidata evolves.

License and attribution

Licensed under CC BY 4.0. Required attribution: "Data by Audiala — audiala.com".

Citation

@misc{audiala-places-2026,
  title  = {Audiala Places: Curated Multilingual Travel POIs},
  author = {{Audiala}},
  year   = {2026},
  url    = {https://audiala.com},
  note   = {CC BY 4.0}
}