NIH expects full transparency in reporting experimental details so that others may reproduce and extend the findings. This session will discuss ways to report experimental details including: open dissemination of methodology protocols, pre-registration of study protocols, and publication of registered reports (subject matter: secure & ethical data use).
The NIH Policy for Data Management and Sharing (NIH DMSP) went into effect on January 25, 2023 and requires NIH-funded researchers to prospectively submit a plan outlining how scientific data from their research will be managed and shared.
Audience: Any NIH-funded researcher
This workshop aims to empower researchers with the essential skills needed to utilize bioinformatics tools operated through the Command Line Interface. It will cover Unix/Linux shell navigation, FTP transfers, file, and directory management, text editor functions, shell scripting, and data analysis with bioinformatics software.
OSF (Open Science Framework) is a free platform for hosting and collaborating on datasets, documentation, and research results to make research more FAIR (Findable, Accessible, Interoperable, and Reusable.) In this workshop, we will tour OSF, discuss the principles of open science in our fields, and work through a sample project together.
Note: OSF also has a sub-site, OSF Registries, for pre-registering studies and systematic reviews. This class will not discuss preregistration in detail, but the underlying website architecture is the same.
If you’ve ever uploaded data or analysis code to a public repository, you may have been prompted to choose a license from dozens of options. But what’s the difference between the GNU license vs. MIT license? What does Creative Commons actually do? And how do licenses interact with copyright and formal Data Use Agreements? This session will explain the basics of licensing and help participants choose an appropriate license for their openly-accessible research products. It is not legal advice or opinion and does not discuss commercialization.
This class covers the creation of data visualizations using the ggplot2 package in R. This is a flipped class and the third part of a series: Introduction to R; Data Wrangling in R, and Data Visualization in R. Upon registration, you will receive links to workshop materials (PowerPoint slides, lecture videos, and practice exercises) that you can view on your schedule. During the class, you will learn how to solve the exercise problems.
Are you curious about version control and project management with Github, but haven't had an opportunity to test out all of its features? Attend this hands-on workshop to work through solo and group exercises that will let you explore tasks like cloning a collaborator's project, making and investigating file changes, and resolving conflicts between versions.
This class is open to all, but especially intended for people working on long-term projects with data or text files or anyone writing code.
The FAIR Data Principles are a set of guiding principles to make data Findable, Accessible, Interoperable and Reusable. In this session, we will review these principles, discuss the challenges of data sharing, and offer practical tips for how sharing can be integrated into a researchers workflow.
Need to find a dataset to act as a control for your study? Or do you want to reuse open access data? This workshop offers tips for locating and citing data, and includes hands-on exercises to explore directories of data repositories and data journals.
OpenRefine is a powerful, free, open source, tool for working with messy tabular data. It runs offline in a web browser and allows for reproducibility in data cleaning. This is a hands-on workshop.
Audience: Faculty, Staff, and Students