kepler.gl, creating data-driven maps becomes a straightforward process. It
supports you with powerful and intuitive functionalities to create beautiful
data-driven maps and gain quick insights from location data. kepler.gl is built
on Deck.gl, which is a WebGL* framework for visual data analysis based on large
kepler.gl was developed in 2018 by Uber and contributed to the Urban
Computing Foundation in 2019. It is distributed under the MIT open source
license. kepler.gl is highly customizable, and it can be embedded in
applications or used in web browser.
and extension in any modern web browser.
How can this Kepler.gl help
Working with kepler.gl is easy for both
technical and non-technical users.
With kepler.gl, the visualization of large
amount of location data within the web browser or application becomes a
straightforward process, helping not merely with visualization but also with
gaining insights from data. It comes with various interactive functionalities such
as filters and playback over time. In this way, it can be used for
visualization and data analysis in different projects with a geospatial
To get a first impression and inspiration please have a look at the sample use cases and maps.
How can I use Kepler.gl
and what are its benefits?
The easiest way to get started with Kepler.gl is using your web browser. Create your first map in only a few steps. Kepler.gl is a client-side application with no server backend. That means your data lives only on your browser and is not sent to any server.
The usual Kepler.gl workflow is
- Add data to the map
- Create data layers
- Add filters
- Customize your map
- If needed: save your
map as an image and export it as a json file
For developers: For more information on how to embed Kepler.gl in your own application please visit Kepler.gl on GitHub.
Country of origin: US
Institution: Urban Computing Foundation – contributed by Uber Corp
Categories: Data Visualization, Open Source, Special Issue
Tags: application, data driven, data science, data visualization, framework, geospatial, map, open source, tool, web-based
Target group: Data scientists, map enthusiasts, developer
image: Brigitte Braun, screenshot of demo data from www.kepler.gl/demo/world_flights, april 2020