Add more information to the readme and goals

Project.toml

@@ -1,7 +1,7 @@
 name = "DynamicalSystems"
 uuid = "61744808-ddfa-5f27-97ff-6e42cc95d634"
 repo = "https://github.com/JuliaDynamics/DynamicalSystems.jl.git"
-version = "3.2.1"
+version = "3.2.2"
 
 [deps]
 Attractors = "f3fd9213-ca85-4dba-9dfd-7fc91308fec7"

README.md

@@ -6,10 +6,17 @@
 [![Textbook](https://img.shields.io/badge/Textbook-10.1007%2F978--3--030--91032--7-purple)](https://link.springer.com/book/10.1007/978-3-030-91032-7)
 [![Package Downloads](https://shields.io/endpoint?url=https://pkgs.genieframework.com/api/v1/badge/DynamicalSystems)](https://pkgs.genieframework.com?packages=DynamicalSystems)
 
-**DynamicalSystems.jl** is an [award-winning](https://dsweb.siam.org/The-Magazine/Article/winners-of-the-dsweb-2018-software-contest) Julia software library for nonlinear dynamics and nonlinear timeseries analysis. The current repository holds the documentation and exports all packages composing DynamicalSystems.jl.
+**DynamicalSystems.jl** is an [award-winning](https://dsweb.siam.org/The-Magazine/Article/winners-of-the-dsweb-2018-software-contest) Julia software library for nonlinear dynamics and nonlinear timeseries analysis.
+Highlights of the library include:
 
-To install it, run `import Pkg; Pkg.add("DynamicalSystems")`.
+- **Open source community project**. Built from the ground up entirely on GitHub, **DynamicalSystems.jl** is 100% open source and built by community contributions. Anyone can be a developer of the library. Everyone is welcomed.
+- **Extensive content**. It covers the entire field of nonlinear dynamics. It has functionality for complexity measures, delay embeddings, stability and bifurcation analysis, chaos, surrogate testing, recurrence quantification analysis, and much more. Missing functionality that falls under nonlinear dynamics is welcomed to be part of the library!
+- **Exceptional documentation**. All implemented algorithms provide a high-level scientific description of their functionality in their documentation string as well as references to scientific papers. The documentation features hundreds of tutorials and examples ranging from introductory to expert usage.
+- **Professionally developed**. Extra care is taken so that the source code is clear and easy to follow. The interfaces of the library are designed to be extendable. All implemented functionality is extensively tested.
+- **Performant**. Written entirely in Julia, heavily optimized and parallelized, and taking advantage of some of the best packages within the language, **DynamicalSystems.jl** is _really fast_.
 
-**DynamicalSystems.jl** is part of [JuliaDynamics](https://juliadynamics.github.io/JuliaDynamics/), an organization dedicated to creating high quality scientific software.
+More information on the library goals and features, as well as usage guidance, is provided in the documentation, which you can either find [online](https://juliadynamics.github.io/DynamicalSystems.jl/dev/) or build locally by running the `docs/make.jl` file.
+
+To install **DynamicalSystems.jl**, run `import Pkg; Pkg.add("DynamicalSystems")`.
 
-All further information is provided in the documentation, which you can either find [online](https://juliadynamics.github.io/DynamicalSystems.jl/dev/) or build locally by running the `docs/make.jl` file.
+**DynamicalSystems.jl** is part of [JuliaDynamics](https://juliadynamics.github.io/JuliaDynamics/), an organization dedicated to creating high quality scientific software.

docs/src/index.md

@@ -58,6 +58,7 @@ This makes reproducing these papers difficult, while some times straight-out imp
 
 To achieve these goals we made **DynamicalSystems.jl** so that it is:
 
+0. **Open**: 100% of the development is happening openly on GitHub. The project is driven by contributions of experts or students of the field, beginners or advanced in programming. Anyone can be a developer of the library. Everyone is welcomed.
 1. **Transparent**: extra care is taken so that the source code of all functions is clear and easy to follow, while remaining as small and concise as possible.
 2. **Intuitive**: a software simple to use and understand makes experimentation easier.
 3. **Easy to extend**: this makes contributions more likely, and can motivate researchers to implement their method here, instead of leaving it in a cryptic script stored in some data server, never-to-be-published with the paper.