Inspirations and principles

Nipoppy is inspired by and built upon the previous work of others. These include community standards (e.g. BIDS), tools (e.g. Boutiques), and technologies (e.g. Apptainer).

Nipoppy will always strive to support and contribute to existing open-source community standards and avoid creating a new one. We see Nipoppy as a “dry lab protocol” that glues together existing tools to help adopt open-science and FAIR data principles in practice.

This umbrella effort is guided by following design principles:

Principle	Example implementation in Nipoppy
Specify sequence / ordering of tasks whenever possible	Generate a manifest before anything else!
Optimize for user-oriented modular design	Conceptually, Nipoppy is divided into curate, process, extract modules to match typical research project stages in a neuroimaging lab.
Prioritize lightweight, simpler design over comprehensive functionalities	Nipoppy performs simpler sanity checks at module endpoints instead of sophisticated provenance tracking of the process to ensure reproducibility
Handle collected data “as-is”	Nipoppy doesn’t interfere with the current data collection practice i.e. modify recruitment, assessment, DICOM files
Don’t be a black box	Nipoppy wants to be a hands-on training tool helping researchers to adopt FAIR principles
Build for iterative workflows	FAIR research involves reproducibility, reuse, and replication. Nipoppy tries to simplify these tasks.
There are no stupid GitHub issues or Discord questions!	Nipoppy is by and for the community - we always welcome feedback to improve it!

We do not claim that all of these principles would immediately improve efficiency. However, we do believe that a short-term investment in the adoption of these efforts will result in huge long-term returns for individual researchers, labs, and consortia.