Vega & Vega-Lite
Visualization Grammars

Vega is a declarative format for creating, saving, and sharing visualization designs. With Vega, visualizations are described in JSON, and generate interactive views using either HTML5 Canvas or SVG.
Toolkits
Vega 2.0 offers a full declarative visualization grammar, suitable for expressive custom interactive visualization design and programmatic generation.
new Vega-Lite provides a higher-level grammar for visual analysis, comparable to ggplot or Tableau, that generates complete Vega specifications.
Systems
Lyra is an interactive environment that enables custom visualization design. Without writing any code, designers can create visualizations on-par with hand-coded D3 and Processing.
PoleStar is a web-based visualization specification interface, inspired by Tableau. Analysts can rapidly generate visualizations as part of the data exploration process.
Voyager is a visualization browser for open-ended data exploration. It provides a gallery of recommended visualizations, produced by Compass visualization recommender engine.
Compass is a visualization recommendation engine. Given user query, it suggests visualizations, ranked by both data properties and perceptual principles.
Vega's 3rd Party Integration

ggvis is a data visualization package for R that renders web-based visualizations using Vega. It features a syntax similar in spirit to ggplot2.

Vincent allows you to build Vega specifications in a Pythonic way. It performs type-checking to ensure your specifications are correct, and offers convenience methods that turn Python data structures into Vega specifications.

Vega.jl uses the Julia programming language to generate spec-compliant Vega 2.x visualizations. Vega.jl is integrated with Jupyter Notebook, and provides a high-quality visualization experience for scientific computing.

The MediaWiki Graph extension allows you to embed Vega visualizations on MediaWiki sites, including Wikipedia.

Cedar integrates Vega with the GeoServices from ArcGIS. It adds templated documents for reusable charts that programatically bind to new data sources.