Why publish a tool in nanoHUB?
You'll make your science and engineering products usable, discoverable, and reproducible for learners, educators, researchers, and business professionals.
Advantages of making your simulation tool available via nanoHUB:
- Gain access to a large audience: 1.5 million visitors per year and growing.
- nanoHUB tools are publications, indexed by Web of Science and Google Scholar.
- Secondary citations. Collectively, nanoHUB tools have an h-index of 82.
- Automatic usage data for each tool shows impact. Learn where your users come from, their affiliation, and more.
- nanoHUB's ecosystem has a place for simulation tools in a multitude of fields: materials science, manufacturing, biology, chemistry, physics, electrical and mechanical engineering, and more.
A web-accessible development workflow
- Complete Linux environment
- A multitude of software packages are already installed in nanoHUB
- Submit simulations to high-performance computing resources
- Launch the Workspace or Jupyter tool in your web browser and start working
- Ticketing system provides assistance to developers or technical support
- 99.466% uptime
- Citation tracking
- Control the reuse of your code and assets via licensing
- Question and Answer forum where your tool's users can find help
- User reviews provide feedback
- Easily share your tool on social media
Multiple ways to publish a tool
If you would like to deploy a workflow, creating a Jupyter Workflow will be your best option. If you already have an X11 GUI that you'd like to use, you can create a tool with that method.
Otherwise, choose one of the three primary types of tools that you can publish on nanoHUB: a Rappture tool, a Jupyter Notebook, or Rappture tools invoked within a Jupyter Notebook.
Which is the best for your purposes?
Features / tool type
Notebook / lab
|XML description of tool inputs and outputs||Yes||No||Yes|
|Automatic GUI from tool input/output||Yes||No||No|
|Custom designed visualization for scientific applications||Yes||Yes||Yes|
|Automatic uncertainty quantification||Yes||No||Yes|
|Simulation caching (instant results for previously run cases)||Yes||No||Yes|
|GUI creation||Limited to built-in
|Expertise required||Expertise required|
|Users can see/modify code||No||Yes||Yes|
|Launch several tools||Yes||Yes||Yes|
|Submit jobs to high-performance computing (HPC) resources||Yes||Yes||Yes|
|Best for computationally intensive tools||Yes||No||Yes|
*Rappture to handle tool input/output Jupyter graphical interfaces with tool
Still can't decide? This decision tree will guide you through the process.