ReproNim module for dataprocessing: Reference

Reproducible research requires understanding all pieces of the (data) workflow

You should be familiar with the necessary elements and tools for reproducible analysis.

Reproducible analysis is technologically possible

Learning these technologies can help produce more reliable research output

Using such frameworks provide a better way to communicate information to colleagues and collaborators

What different file formats store and knowing where to find information

Using standards to simplify harmonization

Hardware and software comprise an analysis environment.

Software and hardware components interact through command options and environment variables.

Dataflow tools create abstraction of process from data.

Dataflow tools allow reuse and composition of tools.

Continuous Integration makes software development more efficient.

Continuous Integration platform can be easily used with a GitHub account.

Analysis can be captured in a way to repeat it

Understanding points of human interaction and decision making are essential for reproducibility