Webinar: 1001 Reasons for a Data Management Plan - with Elixir GermanyData Management Plans (DMPs) are an essential component of research projects, providing a structured framework to ensure that data is adequately documented, organised, shared, and preserved throughout the research lifecycle. In this webinar, we provide an introduction to data management plans, discussing key aspects of effective data management and how to develop a comprehensive data management plan.
This webinar was presented by Daniel Wibberg and Helena Schnitzer, Training Coordinators from Elixir Germany for de.NBI.
FAIR in (biological) practice - Part 06 - Being PreciseThis video is part of the recording from the course FAIR in (biological) practice organised and taught by EMBL Bio-IT, EMBL OSiM, and GHGA.
The course is based on the Software-Carpentries course with the same name, which is currently still in development (Alpha version). You can find the full carpentries materials here: https://carpentries-incubator.github.io/fair-bio-practice/
All the materials and questions discussed in this video can be found here: https://carpentries-incubator.github.io/fair-bio-practice/06-being-precise/index.html
Webinar: A Beginner’s Guide to GalaxyThe webinar explains how you can use Galaxy to analyze your data, where you can find tutorials for Galaxy, and which data you can analyze with the platform. In addition, it dives shortly into the world of workflow languages and describes how you can create your own data processing/analysis pipeline without programming knowledge. At the end, the webinar presents useful options to interact with the Galaxy community to become an active contributor to one of the largest open-science projects in the world.
Webinar: Concepts in Biological Hypothesis TestingHaving a good understanding of statistics is vital for Biologists designing and analysing their own experiments.
To get you started, this webinar covers the general concepts behind hypothesis testing workflows, including summary statistics, null and alternative hypotheses, and p-values. We focus specifically on what you should pay attention to when you interpret results from a biostatistical analysis. We're using gene expression as an example, and work with visuals rather than equations, to make the topic accessible to a broader audience.
This webinar was given by Sarah Kaspar from the Centre for Statistical Data Analysis, EMBL.