Enabling Reproducibility in Data Science
In Focus: Reproducible Data
How do I make sure that independent researchers will be able to reproduce my research results? Why is that even important and what tools or methods are there to achieve this goal? Keeping reproducibility in mind from the very start of a project will help you in the long run and greatly add to the quality of your research. In this event organized by the Helmholtz Open Science Office and HIDA, we will focus on digital reproducibility and best practices for data science.
We will start off the event with two short lectures on reproducibility, first in the context of open science and second in relation to machine learning. Afterwards, you will have the choice to attend and actively take part in one of these three workshops:
- Practical steps towards reproducible research
- Foundations of research software publication
- Scientific metadata: Fundamentals of structured and standardized research data annotation
Speakers
Silke Christine Gerlich is a Postdoctoral Associate in the Helmholtz Metadata Collaboration (HMC) Hub Information, hosted at Forschungszentrum Jülich (FZJ) Institute for Materials Data Science and Informatics (IAS-9). She holds a PhD in Molecular Plant Physiology and contributes to the German National Research Data Infrastructure (NFDI) consortium DataPLANT with a special interest in ontology development.
Tobias Schlauch is working for the institute for software technology at the German Aerospace Center (DLR) since 2005. He contributed to different research projects as software engineer with regard to workflow and data management and supported them in context of software quality assurance. Since 2009, he serves as the representative of the DLR software engineering initiative.
Heidi Seibold is an expert for open and reproducible research, with a focus on data science and health research. She is the host of two podcasts: "Open Science Stories" and ">reboot academia". You can follow Heidi on Twitter under @HeidiBaya.
Peter Steinbach is a trained particle physicist and currently leads the Helmholtz AI consulting team at Helmholtz-Zentrum Dresden-Rossendorf. He is passionate about applied statistics, machine learning and HPC if used appropriately.
Annika Strupp is a Data Steward in the Helmholtz Metadata Collaboration (HMC) Hub Information, hosted at Forschungszentrum Jülich (FZJ) Institute for Materials Data Science and Informatics (IAS-9). She worked as a Web Analytics Consultant in Marketing Technology before joining HMC. She is an extra-occupational masters's student in Digital Data Management (DDM) at Humboldt-Universität zu Berlin and Potsdam University of Applied Sciences (FHP).
Organizers
The Helmholtz Open Science Office supports the Helmholtz Association as a service provider in shaping the cultural change towards open science. It represents Helmholtz in various open science initiatives, is involved in third-party funded projects, and in this way communicates the Helmholtz positions on open science on a national and international level.
HIDA - the Helmholtz Information & Data Science Academy - is Germany’s largest postgraduate training network in the field of information and data science. We prepare the next generation of scientists for a data-heavy future of research.
