✅ Manage your projects

Oct 23, 2023 · 2 min read
Image credit: Unsplash
Date
Oct 23, 2023 12:00 AM

Easily manage your projects - create ideation mind maps, Gantt charts, todo lists, and more!

Ideation

Wowchemy supports a Markdown extension for mindmaps.

Simply insert a Markdown code block labelled as markmap and optionally set the height of the mindmap as shown in the example below.

Mindmaps can be created by simply writing the items as a Markdown list within the markmap code block, indenting each item to create as many sub-levels as you need:


```markmap {height="200px"}
- Hugo Modules
  - wowchemy
  - blox-plugins-netlify
  - blox-plugins-netlify-cms
  - blox-plugins-reveal
```

renders as

- Hugo Modules
  - wowchemy
  - blox-plugins-netlify
  - blox-plugins-netlify-cms
  - blox-plugins-reveal

Diagrams

Wowchemy supports the Mermaid Markdown extension for diagrams.

An example Gantt diagram:

```mermaid
gantt
section Section
Completed :done,    des1, 2014-01-06,2014-01-08
Active        :active,  des2, 2014-01-07, 3d
Parallel 1   :         des3, after des1, 1d
Parallel 2   :         des4, after des1, 1d
Parallel 3   :         des5, after des3, 1d
Parallel 4   :         des6, after des4, 1d
```

renders as

gantt section Section Completed :done, des1, 2014-01-06,2014-01-08 Active :active, des2, 2014-01-07, 3d Parallel 1 : des3, after des1, 1d Parallel 2 : des4, after des1, 1d Parallel 3 : des5, after des3, 1d Parallel 4 : des6, after des4, 1d

Todo lists

You can even write your todo lists in Markdown too:

- [x] Write math example
  - [x] Write diagram example
- [ ] Do something else

renders as

  • Write math example
    • Write diagram example
  • Do something else

Did you find this page helpful? Consider sharing it 🙌

Wowchemy Markdown
Zheng Liu
Authors
Zheng Liu
Assistant Professor
Zheng Liu joined the University of Michigan-Dearborn Industrial and Manufacturing Systems Engineering Department as an Assistant Professor. His research bridges theoretical and applied aspects of AI in manufacturing and energy systems. He focused on physics-based modeling, physics-informed machine learning, and generative design for manufacturing and energy storage applications. He also evaluated the manufacturing processes through life cycle assessment and techno-economic analysis, helping the team win $1M Department of Energy’s (DOE) inaugural American-Made Geothermal Lithium Extraction Prize. He has collaborated on multiple projects funded by the National Science Foundation (NSF) through the Future Manufacturing Research Grant (FMRG) program, as well as the Office of Naval Research (ONR). In addition, he served as a graduate fellow and STEM outreach coordinator at the NSF Engineering Research Center for Power Optimization for Electro-Thermal Systems (POETS). Zheng has received the Sharp Outstanding Graduate Student Award and the Tau Beta Pi Outstanding Graduate Student Award in recognition of his research contributions. He has published more than 15 peer-reviewed journal articles and 15 conference proceedings, and has served as a track chair for the IEEE Transportation Electrification Conference. Through his work, he continues to push the frontiers of AI-driven innovation in manufacturing and energy systems.