This webinar outlines how to use the free Open Science Framework (OSF) as an Electronic Lab Notebook for personal work or private collaborations. Fundamental features we cover include how to record daily activity, how to store images or arbitrary …
This lesson shows how to use Python and skimage to do basic image processing. With support from an NSF iUSE grant, Dr. Tessa Durham Brooks and Dr. Mark Meysenburg at Doane College, Nebraska, USA have developed a curriculum for teaching image …
This video will introduce how to calculate confidence intervals around effect sizes using the MBESS package in R. All materials shown in the video, as well as content from our other videos, can be found here: https://osf.io/7gqsi/
Welcome to R! Working with a programming language (especially if it’s your first time) often feels intimidating, but the rewards outweigh any frustrations. An important secret of coding is that even experienced programmers find it difficult and …
Data Carpentry lesson to learn how to work with Amazon AWS cloud computing and how to transfer data between your local computer and cloud resources. The cloud is a fancy name for the huge network of computers that host your favorite websites, stream …
Data Carpentry lesson to understand data structures and common storage and transfer formats for spatial data. The goal of this lesson is to provide an introduction to core geospatial data concepts. It is intended for learners who have no prior …
Data Carpentry lesson to open, work with, and plot vector and raster-format spatial data in R. The episodes in this lesson cover how to open, work with, and plot vector and raster-format spatial data in R. Additional topics include working with …
This is a recording of a 45 minute introductory webinar on preprints. With our guest speaker Philip Cohen, we’ll cover what preprints/postprints are, the benefits of preprints, and address some common concerns researcher may have. We’ll show how to …
The goal of this lesson is to provide an introduction to R for learners working with geospatial data. It is intended as a pre-requisite for the R for Raster and Vector Data lesson for learners who have no prior experience using R. This lesson can be …