↓Skip to main content
  1. Objectives/

Build tools for reproducible, shareable science

The emphasis is on creating software, workflows, and infrastructure that make data processing, analysis, and sharing reliable and repeatable. By providing versioned datasets, pipelines, and tooling (for example for neuroimaging and behavioral measurements), the aim is to reduce technical barriers, minimize errors, and help researchers reproduce results and reuse resources across projects.

Psychoinformatics

REMODNAV FAIRly big processing workflow Promote open science through shared data and collaboration Build tools for reproducible, shareable science Integrate psychology with informatics Probe brain function with naturalistic, high-dimensional studies Self-hosted research IT infrastructure Adina Wagner Alex Waite Ayan Sengupta Benjamin Poldrack Christian Häusler Christian Mönch Daniel Kottke Emanuele Porcu Falko Kaule Jenna Swarthout Goddard Laura Waite Leonardo Muller-Rodriguez Małgorzata Wierzba Manuel Bayer Michael Burgardt Michael Hanke Michael Notter Michał Szczepanik Moritz Boos Odelfa Songong Pierre Ibe Richard Dinga Stephan Heunis Sven Buchholz Tosca Heunis Venkatesh Hariharapura Shivashankar Vittorio Iacovella Lab-in-a-box Distribits Accessing Behavior for Clinical Data and Joint Usage DataLad Organized Research Information: Ontology-mapping, Curation, Orchestration Key Mechanisms of Motor Control in Health and Disease Study Forrest Data Management for Computational Modelling