Frictionless Data is a suite of open source software, tools, and specifications, with our main reference code in Python, that aims to reduce “frictions” in working with data so users can progress from data to insight faster. Over the past year and a half, we have been working specifically with the researcher community to prototype using Frictionless Data’s open source tools to improve researchers’ data workflows and champion open science. This talk will discuss the technical ideas behind Frictionless Data by showcasing a recent collaborative use case with oceanographers. Together, we implemented Frictionless Data Python code into their data ingest pipelines to integrate disparate data while maintaining quality metadata in an easy to use interface.