Physiopy Community

ReproNim Webinar 01.11.2024

The Physiopy Community, 2024

	github.com/physiopy
	physiopy.github.io physiopy-community-practices.rtfd.io
	physiopy.community@gmail.com s.moia.research@gmail.com

Working towards accessible and reproducible physiological data integration in neuroimaging studies

Physiopy: the community

1.

Community guidelines

2.

BIDS: phys2bids & BEP

3.

Peakdet & phys2denoise

4.

Coming up next...

5.

Why physiopy

In neuroimaging, integration of physiological measures to data collection and analyses are still a niche topic. By raising awareness, we can inspire researchers and clinicians become interested in the topic.

*Open Source Software Development is the idea of developing a software publicly, sharing it from the beginning of the development, fostering a democratic community of contributors in support of the project, using version control and software testing.

physiopy adopts a Community driven, BIDS-based, Open Development* approach, aimed at bringing governance back to the users.

Sharing physiological data, toolboxes, and documentation following the concepts of Open Science could improve the exposition to this topic.

Community practices meetings, community consensus, and community guidelines.

Spark interest!

The more we share, the better it becomes

This is (not)
the way!

Of the People, by the People, for the People

physiopy's aims

The main goal of physiopy is to help collect, analyze and share physiological data by:

Writing packages to make user-friendly pipelines to work with physiological data.
Specializing in physiological data use in neuroimaging (i.e. MRI) data analysis.
Providing documentation containing tips and strategies on how to collect such data and use our packages.
Helping set a standard for these data, albeit without forcing users to use it.

Core components

A set of easily adoptable toolboxes

Community of users, developers, and researchers interested in physiology

Clear and approachable documentation

Community practices based on consensus

Core components

physiopy's projects

Raw data

BIDSification

phys. data preprocessing
(peak detect.)

phys. denoising

phys. imaging

Data acquisition

Process description

QA/QC

physiopy's projects

Raw data

phys2bids

peakdet

phys2denoise

phys. imaging

Data acquisition

physiopy's documentation
&

Coordinated testing suite

BIDS Extension Proposal

physioQC

Physiopy's Community Practices

physiopy's projects

Raw data

phys2bids

peakdet

phys2denoise

phys. imaging

Data acquisition

physiopy's documentation
&

Coordinated testing suite

BIDS Extension Proposal

physioQC

Physiopy's Community Practices

prep4phys

physiopy's status

Highly inspired by the tedana community and The Turing Way
Founded in 2019 by 9 people in 3 labs (during the DC Code Convergence 2019!)
It now counts over 35 contributors from over 25 institutions (not all currently active)
All contributors are recognised via all-contributors schema and authorship, alphabetically
All volunteers are... volunteering (so far) - and development spikes during Brainhacks
The project had virtually no funds (so far)
We are now rediscussing governance, based on the Minimal Viable Governance model
We are also restructuring contributors' guidelines, to make them more friendly!

physiopy's tricks

We tend to automatise as much as possible, also to lower barriers to contribution
We style our code, automated by pre-commit
We release on pipy using semantic versioning (docs in YYYY.m.f), automated by Auto
We assign DOI to every(-ish) release using Zenodo
We release documentation on Read the Docs using restructured text and markdown
All software is released under Apache 2.0 (Practices adopt CC-BY-SA 4.0)
Installation is minimalistic and relies on extra features