ReproNim module for dataprocessing

This lesson is a template for creating ReproNim lessons.

It is based on the lesson template used in Neurohackweek, Data Carpentry and Software Carpentry workshops.


09:00 Module overview What do we need to know to conduct reproducible analysis?
09:10 Lesson 1: Core concepts using an analysis example What are the different considerations for reproducible analysis?
10:40 Lesson 2: Annotate, harmonize, clean, and version data How to work with and preserve data of different types?
12:40 Lesson 3: Create and maintain reproducible computational environments Why and how to use containers and Virtual Machines?
13:40 Lesson 4: Create reusable and composable dataflow tools How to use dataflow tools?
13:55 Lesson 5: Use integration testing to revalidate analyses as data and software change Why and how do we use continuous integration?
13:55 Lesson 6: Track provenance from data to results Can we represent the history of an entire analysis?
Can we use this history to repeat the analysis?
14:40 Finish