The FAIR Principles for Data and Software

The FAIR principles are a set of guidelines for optimising the reuse of research data and software. Adopting them in our research can improve the visibility, efficiency, and impact of our work, in addition to aiding reproducibility and promoting open science practices. [Read More]

Rust for Reproducible Research

Alastair made the case for Rust as a language choice for reproducible computational research, contrasting it with popular languages and exemplifying some of the language features that can help researchers to write safe, robust, reusable code. [Read More]

Speeding up R for Data Analysis

Stuart discussed a variety of methods to speed up your data analysis in R, covering a wide range of topics including: vectorisation, linking datasets, data.table, larger than memory datasets, duckdb, and Rcpp. [Read More]
Tags: R data science