Authored by @DN 

The Data Pipelining paradigm has surprisingly close links with the Maker community.  Members of this latter community fabricate innovative, clever, and beautiful things which, though they may use interesting electronics, live within the physical world.

In the Pipeline Pilot community we try to make innovative, clever, and yes beautiful things which live in the digital world.  What really makes this work well is the materials we have to work with -- the component model, where we can easily grab things to use in our assembly.  This makes things come together surprisingly quickly.

In a post to the BIOVIA Blog, I go into a bit more detail using a specific example around formulations informatics.  There has always been considerable value to be obtained by approaches which use machine learning, but innovation continues to happen in the functional form of the models, meaning they require many fewer experiments to fit.

Luckily for me, most of the code to enable this approach already exists.  It only took a bit of time with the "digital glue gun" to assemble a working application/artwork.

  Low Code No Code ​​​​​​​