Artificial Google Location Data for Software Development

In this post, we are going deeper into the Dynamic Data project, looking at the Google Location dynamic data (library available here on GitHub and at NPM). Opening the library, you’ll see there are four types of data objects: Activity, Location, Places, Routes.

Learn more about dynamic data generators and the benefits of artificial data in software development.

Google Logo

About the data source

Google is one of the largest technology companies in the world, with several of their products being market leaders in their space such as YouTube (video sharing), Google.com (Search Engine), Google Maps (navigation), Google Chrome (web browsing), and much more. As a result, the data that Google can harvest from the user, and the user can request back from Google, is some of the richest available. For the purposes of this blog post, we would like to focus on the user's location history.

Google Location History is an opt-in feature of a Google Account that tracks and stores the locations and routes visited, and the movement behavior of the users mobile phone, so long as the user:

• is signed into their Google Account
• has Location History enabled in their Google Account
• has Location Reporting enabled on the device connected to their Google Account

Google then uses this data to enhance their products and services to the user through personalized ads, recommendations, etc. By using Google Maps Timeline, the user can access and view all of their location history data. The user can export their location history through Google Takeout as a collection of JSON objects stored in a .zip folder.

Example Image of Google Location History

Approach used

As stated in the above section, several JSON objects were exported from Google Takeout and stored in a NPM package. The index file of the package imports these data objects and exports them as a collection called “Data”. These mockup files make up the google-data package

Activity

Location

Places

Routes

Models Generated With JSON Crack

The google-mockups package imports the files above and goes through each attribute generating artificial (new) data using proprietary functions, such as those found in the utils package.

For example, with the Route object:

Static Route Object

Artificial Route Object

Use case ideas

• Location Apps
  
• Data Visualization apps
  
• etc

Ideas to combine with some other data sources

• Using Fitbit, Whoop, Withings, etc. to show Fitness Stats during location routes
  
• Using Uber, to show trip details with the locations visited, routes taken, etc.
• Or with some entirely different segment data, like air quality, weather or similar to find interesting new applications for the data.

Open-source data library

We welcome contributions and forks to this data set, and look forward to seeing what developers build in our Liberty. Equality. Data. Slack channel.

Considerations for next version/improvements

• Proper usage of the utils package
• Suitable dates recorded for the faked data
• Reasonable routes/distances
• Sensible Location data
  

With Prifina developers can use the Dynamic Data Libraries natively in the App Studio to build direct to consumer apps where individuals can run them with their own user-held data.

Join our Slack community; Liberty. Equality. Data. to brainstorm and collaborate with other app developers, designers, and our team.