Evolving FSQ Open Source Places
Foursquare has transitioned its OS Places dataset to a new portal to enhance community engagement and data improvement. The dataset has seen significant growth in usage and contributions, with millions of edits proposed by users. This evolution aims to connect dataset consumers with the opportunity to contribute, fostering a cycle of better data and applications.
- ▪The OS Places dataset is now accessed through a new Places portal, allowing users to register and retrieve data.
- ▪Monthly downloads of the dataset have increased to over 3000 on HuggingFace, with more than 250k queries executed on Snowflake.
- ▪The Placemaker community has proposed over 27 million edits in the past year, demonstrating the effectiveness of community-driven data maintenance.
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Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Foursquare |
| Canonical URL | https://foursquare.com/resources/blog/data/evolving-fsq-open-source-places/ |
| Publication time | Fri, 29 May 2026 10:12:39 +0000 |
| Retrieval time | 2026-05-29T10:20:00.361Z |
| Last seen | 2026-05-29T10:20:00.361Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | M5WTdDvKDXYa |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Resources / Blog / Data Evolving FSQ Open Source Places October 8, 2025 by Vikram Gundeti In November 2024, we took a bold step in open-sourcing our Places dataset with a hypothesis that a community driven approach is the only way to create a sustainable and robust places dataset that can serve the needs of diverse problem domains. Our thesis has been validated with the tremendous progress we have been able to make in improving this open dataset since its inception. Increased adoption: Our S3 listing is downloaded from more than 5000 unique IPs every month, a steady increase from 500 unique IPs when we first launched. More than 250k queries are executed on our Snowflake listing every month. And we have 3000+ monthly downloads of our dataset on HuggingFace.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Foursquare.
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