diff --git a/README.md b/README.md
index 0b06ab8..7afb289 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
 # About
 
-This project is part of the source of [The Apache ECharts (incubating) Official Website](https://echarts.apache.org/). See [incubator-echarts-website](https://github.com/apache/incubator-echarts-website) for more details of the building process.
+This project is part of the source of [The Apache ECharts Official Website](https://echarts.apache.org/). See [echarts-website](https://github.com/apache/echarts-website) for more details of the building process.
 
 ## Init
 
@@ -40,12 +40,12 @@
 xxxx [series.encode](${optionPath}#series.encode) xxxx
 ```
 
-Note: if you want it to work in development environment, you may need to edit the config file `configs/config.dev.js`: make the value of `optionPath` point to a running environment of `incubator-echarts-doc`.
+Note: if you want it to work in development environment, you may need to edit the config file `configs/config.dev.js`: make the value of `optionPath` point to a running environment of `echarts-doc`.
 
 
 ### Reference to an example
 
-Suppose `area-basic` is one of the example names in `incubator-echarts-examples`.
+Suppose `area-basic` is one of the example names in `echarts-examples`.
 
 Just add a link of the example:
 ```md
@@ -57,5 +57,5 @@
 <iframe width="600" height="300" src="${exampleViewPath}area-basic&edit=1&reset=1"></iframe>
 ```
 
-Note: if you want it to work in development environment, you may need to edit the config file `configs/config.dev.js`: make the value of `exampleViewPath` and `exampleEditorPath` point to a running environment of `incubator-echarts-examples`.
+Note: if you want it to work in development environment, you may need to edit the config file `configs/config.dev.js`: make the value of `exampleViewPath` and `exampleEditorPath` point to a running environment of `echarts-examples`.
 
diff --git a/build/generate.js b/build/generate.js
index a3b3065..ed50671 100644
--- a/build/generate.js
+++ b/build/generate.js
@@ -6,7 +6,7 @@
       bootstrapCSS: 'https://cdn.jsdelivr.net/npm/bootstrap@3.3.7/dist/css/bootstrap.min.css',
       bootstrapJS: 'https://cdn.jsdelivr.net/npm/bootstrap@3.3.7/dist/js/bootstrap.min.js'
   },
-  cdnPayRootMap: 'https://cdn.jsdelivr.net/gh/apache/incubator-echarts-website@asf-site'
+  cdnPayRootMap: 'https://cdn.jsdelivr.net/gh/apache/echarts-website@asf-site'
 };
 
 let template = `<!DOCTYPE html>
@@ -36,7 +36,7 @@
 updateNav('en');
 
 function updateNav(locale) {
-    let navContent = fs.readFileSync(`../incubator-echarts-website/${locale}/nav.html`, 'utf-8');
+    let navContent = fs.readFileSync(`../echarts-website/${locale}/nav.html`, 'utf-8');
     navContent = `module.exports = \`${navContent}\`\n`;
     fs.writeFileSync(`./components/partials/Navbar/${locale}.js`, navContent, 'utf-8');
 }
diff --git a/configs/config.asf.js b/configs/config.asf.js
index c54ed6e..a499166 100644
--- a/configs/config.asf.js
+++ b/configs/config.asf.js
@@ -5,5 +5,5 @@
   exampleEditorPath: 'https://echarts.apache.org/examples/zh/editor.html?c=',
   mainSitePath: 'https://echarts.apache.org/',
   optionPath: 'https://echarts.apache.org/option.html#',
-  gitRepo: 'apache/incubator-echarts-handbook'
+  gitRepo: 'apache/echarts-handbook'
 };
diff --git a/configs/config.dev.js b/configs/config.dev.js
index cd410ff..0da05fe 100644
--- a/configs/config.dev.js
+++ b/configs/config.dev.js
@@ -1,9 +1,9 @@
 export default {
   base: '/echarts-handbook/dist',
   rootPath: 'http://localhost:3000/echarts-handbook/dist',
-  exampleViewPath: 'http://localhost/incubator-echarts-website/examples/zh/view.html?c=',
-  exampleEditorPath: 'http://localhost/incubator-echarts-website/examples/zh/editor.html?c=',
-  mainSitePath: 'http://localhost/incubator-echarts-website/',
-  optionPath: 'http://localhost/incubator-echarts-website/option.html#',
-  gitRepo: 'apache/incubator-echarts-handbook'
+  exampleViewPath: 'http://localhost/echarts-website/examples/zh/view.html?c=',
+  exampleEditorPath: 'http://localhost/echarts-website/examples/zh/editor.html?c=',
+  mainSitePath: 'http://localhost/echarts-website/',
+  optionPath: 'http://localhost/echarts-website/option.html#',
+  gitRepo: 'apache/echarts-handbook'
 };
diff --git a/contents/en/best-practice/canvas-vs-svg.md b/contents/en/best-practice/canvas-vs-svg.md
index f851289..0b53b15 100644
--- a/contents/en/best-practice/canvas-vs-svg.md
+++ b/contents/en/best-practice/canvas-vs-svg.md
@@ -2,7 +2,7 @@
 
 Most of the browser-side chart libraries are using SVG or Canvas as their underlying render because they are interchangeable. However, they show notable differences in some specific scenarios and cases. As a result, it is hard to find a standard choice between them.
 
-Canvas has been used as the renderer (VML for IE8-) of ECharts from the beginning. Since [ECharts v4.0](https://github.com/apache/incubator-echarts/releases) was released, ECharts provided the SVG render as an additional option. You can specify the [renderer parameter](http://echarts.baidu.com/api.html#echarts.init) as `'canvas'` or `'svg'` while initializing a chart.
+Canvas has been used as the renderer (VML for IE8-) of ECharts from the beginning. Since [ECharts v4.0](https://github.com/apache/echarts/releases) was released, ECharts provided the SVG render as an additional option. You can specify the [renderer parameter](http://echarts.baidu.com/api.html#echarts.init) as `'canvas'` or `'svg'` while initializing a chart.
 
 > SVG and Canvas have a significant difference in use. The simultaneous transparent support in ECharts between SVG and Canvas is because of the abstraction and implementation of the underlying library [ZRender](https://github.com/ecomfe/zrender). It formed an interchangeable SVG renderer and Canvas renderer.
 
@@ -21,7 +21,7 @@
 	+ To create a huge amount of instance in a crash-prone browser (It perhaps because the number of Canvas exceeded the capacity of the phone.), Try to use SVG renderer to improve. Generally, if the chart is running on a low-end Android phone, or you are using some specific chart like [liquidfill](https://ecomfe.github.io/echarts-liquidfill/example/), the SVG render will perform better.
 	+ Use Canvas while visualizing a large amount of data.
 
-We strongly welcome developers to give us a [feedback](https://github.com/apache/incubator-echarts/issues/new). It will be very helpful for us to optimize ECharts. Thank you!
+We strongly welcome developers to give us a [feedback](https://github.com/apache/echarts/issues/new). It will be very helpful for us to optimize ECharts. Thank you!
 
 Note: except some specific charts rely on Canvas (eg. [series lines effect](option.html#series-lines.effect), [heatmap bmap](examples/editor.html?c=heatmap-bmap), etc.), most of the remaining render are supported by SVG. SVG can not support rich text, texture, and shadow right now.
 
diff --git a/contents/en/concepts/data-transform.md b/contents/en/concepts/data-transform.md
index c8368c9..2030667 100644
--- a/contents/en/concepts/data-transform.md
+++ b/contents/en/concepts/data-transform.md
@@ -1,6 +1,6 @@
 # Data Transform
 
-`Data transform` has been supported since Apache ECharts (incubating)<sup>TM</sup> 5. In echarts, the term `data transform` means that generate new data from user provided source data and transform functions. both This feature is enable users to process data in declarative way, and provides users some common "transform functions" to make that kind of tasks "out-of-the-box". (For consistency in the context, the noun form of the word we keep using the "transform" rather than "transformation").
+`Data transform` has been supported since Apache ECharts<sup>TM</sup> 5. In echarts, the term `data transform` means that generate new data from user provided source data and transform functions. both This feature is enable users to process data in declarative way, and provides users some common "transform functions" to make that kind of tasks "out-of-the-box". (For consistency in the context, the noun form of the word we keep using the "transform" rather than "transformation").
 
 The abstract formula of data transform is: `outData = f(inputData)`, where the transform function `f` can be like `filter`, `sort`, `regression`, `boxplot`, `cluster`, `aggregate`(todo) ...
 With the help of those transform methods, users can be implements the features like:
diff --git a/contents/zh/application/custom-build.md b/contents/zh/application/custom-build.md
index 2ed7579..38dee6a 100644
--- a/contents/zh/application/custom-build.md
+++ b/contents/zh/application/custom-build.md
@@ -1,6 +1,6 @@
 # 自定义构建
 
-一般来说，可以直接从 [CDN](https://www.jsdelivr.com/package/npm/echarts) 中获取构建后的 ECharts，也可以从 [GitHub](https://github.com/apache/incubator-echarts/releases) 中的 `echarts/dist` 文件夹中获取构建好的 echarts，这都可以直接在浏览器端项目中使用。这些构建好的 echarts 提供了下面这几种定制：
+一般来说，可以直接从 [CDN](https://www.jsdelivr.com/package/npm/echarts) 中获取构建后的 ECharts，也可以从 [GitHub](https://github.com/apache/echarts/releases) 中的 `echarts/dist` 文件夹中获取构建好的 echarts，这都可以直接在浏览器端项目中使用。这些构建好的 echarts 提供了下面这几种定制：
 
 - 完全版：`echarts/dist/echarts.js`，体积最大，包含所有的图表和组件，所包含内容参见：`echarts/echarts.all.js`。
 - 常用版：`echarts/dist/echarts.common.js`，体积适中，包含常见的图表和组件，所包含内容参见：`echarts/echarts.common.js`。
@@ -120,7 +120,7 @@
 
 ## 允许被引用的模块
 
-在自定义构建中，允许被引用的模块，全声明在 [`myProject/node_module/echarts/echarts.all.js`](https://github.com/apache/incubator-echarts/blob/master/echarts.all.js) 和 [`myProject/node_module/echarts/src/export.js`](https://github.com/apache/incubator-echarts/blob/master/src/export.js) 中。echarts 和 zrender 源代码中的其他模块，都是 echarts 的内部模块，**不应该去引用**。因为在后续 echarts 版本升级中，内部模块的接口和功能可能变化，甚至模块本身也可能被移除。
+在自定义构建中，允许被引用的模块，全声明在 [`myProject/node_module/echarts/echarts.all.js`](https://github.com/apache/echarts/blob/master/echarts.all.js) 和 [`myProject/node_module/echarts/src/export.js`](https://github.com/apache/echarts/blob/master/src/export.js) 中。echarts 和 zrender 源代码中的其他模块，都是 echarts 的内部模块，**不应该去引用**。因为在后续 echarts 版本升级中，内部模块的接口和功能可能变化，甚至模块本身也可能被移除。
 
 
 ## 引用 `echarts/lib/**` 还是 `echarts/src/**`
diff --git a/contents/zh/basics/download.md b/contents/zh/basics/download.md
index 7e6632d..91472cc 100644
--- a/contents/zh/basics/download.md
+++ b/contents/zh/basics/download.md
@@ -1,6 +1,6 @@
 # 下载
 
-Apache ECharts (incubating) 提供了多种安装方式，你可以根据项目的实际情况选择以下任意一种方式安装。
+Apache ECharts 提供了多种安装方式，你可以根据项目的实际情况选择以下任意一种方式安装。
 
 1. 从官网获取
 2. 从 GitHub 获取
@@ -16,14 +16,14 @@
 
 ### 从官网获取
 
-[Apache ECharts (incubating) 官网下载界面](https://echarts.apache.org/download.html) 提供了镜像网站下载源码，并且核对签名的方式——这可以保证下载的代码与发布的代码一致。
+[Apache ECharts 官网下载界面](https://echarts.apache.org/download.html) 提供了镜像网站下载源码，并且核对签名的方式——这可以保证下载的代码与发布的代码一致。
 
 具体的方法参见[官网下载页面](${mainSitePath}/download.html)。
 
 
 ### 从 GitHub 获取
 
-[apache/incubator-echarts](https://github.com/apache/incubator-echarts) 项目的 [release](https://github.com/apache/incubator-echarts/releases) 页面可以找到各个版本的链接。点击下载页面下方 Assets 中的 Source code，解压后 `dist` 目录下的 `echarts.js` 即为包含完整 ECharts 功能的文件。
+[apache/echarts](https://github.com/apache/echarts) 项目的 [release](https://github.com/apache/echarts/releases) 页面可以找到各个版本的链接。点击下载页面下方 Assets 中的 Source code，解压后 `dist` 目录下的 `echarts.js` 即为包含完整 ECharts 功能的文件。
 
 
 ### 从 npm 获取
@@ -47,11 +47,11 @@
 
 ## 目录结构
 
-下面介绍项目 [`dist`](https://github.com/apache/incubator-echarts/tree/master/dist) 目录下各个文件的意义：
+下面介绍项目 [`dist`](https://github.com/apache/echarts/tree/master/dist) 目录下各个文件的意义：
 
 - `echarts.js`：包含了完整 ECharts 功能的代码，没有经过压缩；推荐调试时使用。
 - `echarts.min.js`：`echarts.js` 的压缩结果；推荐线上使用。
 - `echarts.simple.js`：包含折线图、柱状图、饼图的代码；推荐不需要其他系列类型的项目使用。
-- `echarts.common.js`：包含了常用组件和系列类型的代码，完整支持的内容参见 [echarts.common.js](https://github.com/apache/incubator-echarts/blob/master/echarts.common.js)
+- `echarts.common.js`：包含了常用组件和系列类型的代码，完整支持的内容参见 [echarts.common.js](https://github.com/apache/echarts/blob/master/echarts.common.js)
 
 带有 `-en` 的文件是对应的英文版本，带有 `.min` 的文件是对应的压缩版本。
diff --git a/contents/zh/basics/help.md b/contents/zh/basics/help.md
index 588073f..ec7df8a 100644
--- a/contents/zh/basics/help.md
+++ b/contents/zh/basics/help.md
@@ -12,7 +12,7 @@
 - [配置项手册](${mainSitePath}/option.html)：可以尝试使用搜索功能
 - 本手册的文章
 - [常见问题](${mainSitePath}/faq.html)
-- 在 [GitHub issue](https://github.com/apache/incubator-echarts/issues) 中搜索关键字
+- 在 [GitHub issue](https://github.com/apache/echarts/issues) 中搜索关键字
 - 使用搜索引擎搜索关键字
 
 
diff --git a/contents/zh/best-practice/canvas-vs-svg.md b/contents/zh/best-practice/canvas-vs-svg.md
index 4864232..531c958 100644
--- a/contents/zh/best-practice/canvas-vs-svg.md
+++ b/contents/zh/best-practice/canvas-vs-svg.md
@@ -2,7 +2,7 @@
 
 浏览器端图表库大多会选择 SVG 或者 Canvas 进行渲染。对于绘制图表来说，这两种技术往往是可替换的，效果相近。但是在一些场景中，他们的表现和能力又有一定差异。于是，对它们的选择取舍，就成为了一个一直存在的不易有标准答案的话题。
 
-ECharts 从初始一直使用 Canvas 绘制图表（除了对 IE8- 使用 VML）。而 [ECharts v4.0](https://github.com/apache/incubator-echarts/releases) 发布了 SVG 渲染器，从而提供了一种新的选择。只须在初始化一个图表实例时，设置 [renderer 参数](http://echarts.baidu.com/api.html#echarts.init) 为 `'canvas'` 或 `'svg'` 即可指定渲染器，比较方便。
+ECharts 从初始一直使用 Canvas 绘制图表（除了对 IE8- 使用 VML）。而 [ECharts v4.0](https://github.com/apache/echarts/releases) 发布了 SVG 渲染器，从而提供了一种新的选择。只须在初始化一个图表实例时，设置 [renderer 参数](http://echarts.baidu.com/api.html#echarts.init) 为 `'canvas'` 或 `'svg'` 即可指定渲染器，比较方便。
 
 > SVG 和 Canvas 这两种使用方式差异很大的技术，能够做到同时被透明支持，主要归功于 ECharts 底层库 [ZRender](https://github.com/ecomfe/zrender) 的抽象和实现，形成可互换的 SVG 渲染器和 Canvas 渲染器。
 
@@ -20,7 +20,7 @@
     + 在须要创建很多 ECharts 实例且浏览器易崩溃的情况下（可能是因为 Canvas 数量多导致内存占用超出手机承受能力），可以使用 SVG 渲染器来进行改善。大略得说，如果图表运行在低端安卓机，或者我们在使用一些特定图表如 [水球图](https://ecomfe.github.io/echarts-liquidfill/example/) 等，SVG 渲染器可能效果更好。
     + 数据量很大、较多交互时，可以选用 Canvas 渲染器。
 
-我们强烈欢迎开发者们[反馈](https://github.com/apache/incubator-echarts/issues/new)给我们使用的体验和场景，帮助我们更好的做优化。
+我们强烈欢迎开发者们[反馈](https://github.com/apache/echarts/issues/new)给我们使用的体验和场景，帮助我们更好的做优化。
 
 
 注：除了某些特殊的渲染可能依赖 Canvas：如[炫光尾迹特效](option.html#series-lines.effect)、[带有混合效果的热力图](examples/editor.html?c=heatmap-bmap)等，绝大部分功能 SVG 都是支持的。此外，目前的 SVG 版中，富文本、材质功能尚未实现。
diff --git a/contents/zh/concepts/data-transform.md b/contents/zh/concepts/data-transform.md
index 46db263..20aa5aa 100644
--- a/contents/zh/concepts/data-transform.md
+++ b/contents/zh/concepts/data-transform.md
@@ -1,6 +1,6 @@
 # 使用 transform 进行数据转换
 
-Apache ECharts (incubating)<sup>TM</sup> 5 开始支持了“数据转换”（ data transform ）功能。在 echarts 中，“数据转换” 这个词指的是，给定一个已有的“数据集”（[dataset](${optionPath}#dataset)）和一个“转换方法”（[transform](${optionPath}#dataset.transform)），echarts 能生成一个新的“数据集”，然后可以使用这个新的“数据集”绘制图表。这些工作都可以声明式地完成。
+Apache ECharts<sup>TM</sup> 5 开始支持了“数据转换”（ data transform ）功能。在 echarts 中，“数据转换” 这个词指的是，给定一个已有的“数据集”（[dataset](${optionPath}#dataset)）和一个“转换方法”（[transform](${optionPath}#dataset.transform)），echarts 能生成一个新的“数据集”，然后可以使用这个新的“数据集”绘制图表。这些工作都可以声明式地完成。
 
 抽象地来说，数据转换是这样一种公式：`outData = f(inputData)`。`f` 是转换方法，例如：`filter`、`sort`、`regression`、`boxplot`、`cluster`、`aggregate`(todo) 等等。有了数据转换能力后，我们就至少可以做到这些事情：
 + 把数据分成多份用不同的饼图展现。