Dr. Stephan Heunis is neuroscientist, software engineer and open-science tools enthusiasts. He has an M.Sc. in Biomedical Engineering and Robotics from Stellenbosch University in South Africa. He worked as a commercial and software engineer for four years in two industries (Industrial Automation and Enterprise Mobility) before moving to the Netherlands with the goal of conducting research in neuroscience. His doctoral research at the Eindhoven University of Technology and in collaboration with Philips Research focused on developing new acquisition and signal processing methods for functional magnetic resonance imaging (MRI) that allow improved tracking and visualisation of brain activity in real-time. Stephan is passionate about brains, accessible education, and making scientific practice more transparent and inclusive. Throughout his doctoral research, he has been active in the Dutch network of Open Science Communities and he founded OpenMR Benelux, a community working on wider adoption of open science practices in MRI research through talks, discussions, workshops and hackathons. Stephan has since continued this passion as a Research Data and Software Engineer at the Forschungszentrum Jülich in Germany, where he works on software solutions for neuroinformatics and decentralised research data management. He also holds post-doctoral positions in the SYNC developmental neuroscience lab at Erasmus University Rotterdam and Leiden University in the Netherlands.
Ideally, our scientific outputs, i.e. the data and results from which we draw our inferences and influence decisions, should be reproducible. Reproducibility allows replication and verification of our work, fosters public trust in science, promotes collaboration, and underlies scientific progress. Practically, however, reproducibility is much easier to talk about than to achieve. While challenges stem from various origins, a key challenge relates to the complexity of our data, how we choose to process it (and there are many possibilities!), and the high variance in terms of the infrastructure used by researchers globally. This talk covers some of these practical challenges, and will provide an overview of common tools available to researchers for addressing these challenges. Highlights include git and GitHub, requirements files for software scripts, containers, myBinder and DataLad.