Frequently Asked Questions

Placekey is a free and open universal standard identifier for any physical place, so that the data pertaining to those places can be shared across organizations easily.

Placekey creates a common industry standard for identifying any physical place. Eventually, there will be a Placekey for every place in the world, even those without a postal address (school district, county, neighborhood, etc.).

However, Placekey goes beyond just an identifier. It’s a movement of organizations and individuals that prize access to data. Placekey members want geospatial data that is easily joined and combined…because real answers come from combining data from many different sources. It is a philosophy that data should be easy to access and data should not be hoarded. These members believe that data, when combined, can do massive good.

Absolutely nothing. 

Whether you generate a Placekey via this website or use the Placekey API, it will always be free.* ‍

*Should a business ping the Placekey API with a massive number of requests—in the millions per month, for example—we may invite you to help us cover those computing costs.

Yes. Placekey is meant to be free and used widely.

Over 500 organizations have signed on to support Placekey including Esri, SafeGraph, Carto, and Landgrid. See the full list of Placekey member organizations.

Users will be able to obtain Placekey for each of their places by using the Placekey API. You can read more about the API by visiting our docs or email [email protected] if you want to get involved.

Additionally, some Placekey partners have Placekey as an attribute of their datasets.

Your request data may be stored to improve the match service and better understand the requests that are resolving to specific Placekeys, but they will never be shared or sold to third-parties.

Developers can call into the Placekey API (documentation). In addition, you can work with Placekey in geospatial computations by using one of the community-contributed open-source libraries, on npm (javascript), or on PyPi (python). To collaborate with us, check out our GitHub.

Here is an example of a complete Placekey:

The What Part consists of two unique character sequences. 

The first three characters refer to Address Encoding, creating a unique identifier for a given address. An address at “555 Main Street Suite 105” will have different Address Encoding than “555 Main Street Suite 106.”  

The second set of three characters in the What Part refers to POI Encoding. If a specific place is already included in the Placekey reference datasets, these characters will be present. The benefit of POI Encoding is that it can point to a specific Point-of-Interest that may have existed at a certain address at a given point in time. While Address Encoding allows Placekey to hone in on a specific address, there’s always the chance that either:

1. Multiple businesses can exist at the same address at the same time (i.e. a Starbucks coffee shop within a Target retail store); or
   
   
2. Multiple businesses may have occupied that space over time (i.e. what may have been a Chipotle restaurant a year ago is now a McDonald’s restaurant).

The Where Part, on the other hand, is made up of three unique character sequences, built upon Uber’s open source H3 grid system. This information in the Where Part is based on the center point of that place. In other words, we take the exact latitude and longitude of a specific place and then use a conversion function to determine which hexagon in the physical world contains the centroid of that place. The hexagon is currently fixed at H3’s Resolution 10 (about 15,000 square meters). The Where Part of the Placekey is, therefore, the full encoding of that hexagon.

Geohash uses squares while H3 uses hexagons. What’s so great about hexagons?

• Each neighbor is on an edge so all centers are equidistant. This means that data scientists can easily perform flow analysis between cells without normalization.
• Hexagonal approximations look nicer than rectangular ones in visualizations and do not distort as much as you move around the globe.
• Hexagonal tiling of the globe has low distortion (dymaxion projection with vertices in water).

Additionally, in some instances, the same space can be represented by multiple geohash encodings of the same length. Geohash encodings can spell out inappropriate words (e.g., “jerk” is a valid geohash) or include ambiguous characters such as “o0il1”.

H3 is also open-sourced and has a permissive software license that encourages open and public development. Because of this, it has a vibrant community of contributions, extensions, and collaboration.

Placekey solves a number of industry problems, most notably:

• Effectively joins POI datasets: Addresses are hard to work with for joining datasets. They can be formatted in different ways, lack critical information, and can require deduplicating for accuracy. By having a common Placekey to unify all of these datasets, users can easily combine different datasets. For data providers, Placekey ensures that users can get maximum value out of the data by making it much easier for users to combine internal or external datasets.
  
  
• Effectively joins POI and non-POI datasets: In the same way that a Placekey can serve as a unifier between POI-based datasets, it can also be leveraged to join non-POI datasets with POI data in ways that were never easy before. For example, you can now join weather or elevation data about a specific place just by linking it to the Where Part of any given Placekey.
  
  
• Accounts for places without addresses: Not every physical place comes equipped with an address. In these cases, Placekey can provide users with a description of the physical place in lieu of an address. The Address Encoding for these will be ‘zzz’.
  
  
• Accounts for multiple POIs at a single address: There are many instances where a single address can house multiple POIs. For example, a Starbucks coffee shop inside of a Target retail store or a Panda Express restaurant inside of an airport terminal. The POI Encoding component in the What Part of the Placekey can help distinguish these nuances while preserving the same identifiers in the Address Encoding and Where Part components.
  
  
• Accounts for multiple POIs over time at a single address: It is highly likely that different businesses will inhabit the same physical place over a period of time. For example, what may have been a Starbucks coffee shop three years ago is now a Chipotle restaurant. While the Where Part and the Address Encoding of the What Part of a Placekey will remain consistent regardless of what POI inhabits a given place, the historical POI Encoding of the What Part of a Placekey can tell us exactly what different POIs may have been present in that place over time.
  
  
• Compares the proximity of two POIs easily: The Where Part of a Placekey can help you identify how close two different POIs are to each other based on the number of characters they share in common, when read from left to right.
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• Creates a simplified identification system: We wanted to create a streamlined, easy-to-use identification system for precise places in the physical world that would reduce confusion and minimize the complexity found in other identification systems. To do this, we’ve kept the Where Part of a Placekey ridiculously simple: a unique string of nine alpha-numerical digits that clearly identifies one place over another.

Placekeys are stable on places.  

Of course, places themselves change -- and sometimes they merge with other places.  Sometimes two very different addresses resolve to the same place. And sometimes Placekey will have bugs (we are not perfect).

Once you associate a Placekey on a place, you might want to re-ping the API on that place every 3-5 months in case the Placekey has changed.

Not at this time (but coming soon!). Right now, only places with postal addresses have a unique Placekey.  

In the future, school districts, neighborhoods, and homes that do not have postal addresses will be represented by a Placekey.

This is the easy part. Just by using Placekey you are helping it become an industry standard. You can also help by following and promoting our social channels, including Twitter, Facebook, Linkedin, and Github (where we welcome your contributions to our open source projects). 

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If you’d like to join the growing numbers of businesses sponsoring Placekey, email [email protected] or visit our partners page to get involved.

Plus Codes are intended to help identify locations and typically represent a 14 meter x 14 meter space (roughly the size of half of a basketball court), but can work at multiple resolutions. They were not built to convey POI-related information whatsoever, nor can they distinguish between places on different floors within a building (i.e. specific apartment units) or individual, smaller POIs within a larger footprint (i.e. Starbucks coffee shop within a Target retail store). 

A Placekey can provide all of the information available in a Plus Code but then takes it a big step further by providing an extra layer of POI-related information for added precision that can unlock a wealth of unique insights when joined with multiple datasets.

What3Words is not an open standard and, therefore, cannot be easily used or combined with other datasets to extract meaningful value in the rapidly expanding data marketplace. 

With Placekey, we have built an open and uniform industry-wide standard for identifying physical places in a truly hyper-local way—and have also created a better way to enable users to unify multiple data sources around a single Placekey to drive innovation like never before.