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SciWIn

Scientific Workflow Infrastructure

SciWIn

One workflow format, two ways to work with it. Build, run, and publish reproducible computational workflows from the terminal with SciWIn-Client, or visually with SciWIn-Studio - every project works in both.
Install SciWIn-ClientGet SciWIn-StudioRead the docs
terminal
s4n create python calculation.py --population population.csv --speakers speakers.csv
📂 /home/ubuntu/sciwin_test
⏳ Executing command: python calculation.py …
📜 Found changes: results.csv
📄 Created CWL file workflows/calculation/calculation.cwl
s4n connect main --from calculation/results --to plot/data
➕ Added step calculation to workflow
✔️ Updated Workflow workflows/main/main.cwl!
SciWIn-Studio
SciWIn-Studio graph canvas showing connected workflow nodes
⇄ workflow.toml - same project
Author & run from the command lineWire the same tools together visually

Both write the exact same workflow.toml + CWL files + git repo. Start a tool in one, finish the workflow in the other - nothing to export or convert.

See it on real workflows

Section titled “See it on real workflows”

Every example runs on real data, end to end.

simple workflow

Getting started example

The Guide that gets you started with SciWIn-Client. If you just installed the software it is recommended to start here.

Read the walkthrough →
advanced example

Real world example

A real world example based on real data of election results containing several steps and making use of containerization.

See the workflow →
corn example

Corn Prediction (Iowa)

A simplified crop yield prediction pipeline that combines soil and weather data to train models and generate county-level yield predictions for Iowa.

See the workflow →

Get started

Section titled “Get started”

Pick the side you’ll work from - both open the exact same project.

Terminal

SciWIn-Client

  1. Install s4n. The easiest way is the installer script.

    Linux

    curl --proto '=https' --tlsv1.2 -LsSf https://fairagro.github.io/sciwin/get_s4n.sh | sh

    Windows

    powershell -ExecutionPolicy Bypass -c "irm https://fairagro.github.io/sciwin/get_s4n.ps1 | iex"
  2. Initialize a project in your code repository. 
    s4n init
  3. Record your first tool by prefixing any command with create. 
    s4n create python echo.py "Hello World"
Visual canvas

SciWIn-Studio

  1. Download the latest release for your platform.
  2. Open a folder - a new one, or an existing s4n project.
  3. Drag a CWL file onto the canvas and connect it into a workflow.