Overview

Feel free to choose one or more of the activities below to pursue.

Read

Time estimate: 20 minutes

Let’s consider what it would take to FAIRify things other than data. Read one (or both) of the following, and consider the following questions:

Garcia L, Batut B, Burke ML, Kuzak M, Psomopoulos F, Arcila R, et al. (2020) Ten simple rules for making training materials FAIR. PLoS Comput Biol 16(5): e1007854. https://doi.org/10.1371/journal.pcbi.1007854

Lamprecht et al. (2020) Towards FAIR principles for research software. Data Science 3(1): 37-59. https://doi.org/10.3233/DS-190026

Questions to consider:

  • Which guidelines or rules would be easiest to apply?
  • What contexts or scenarios familiar to your organisation are not met by these rules or guidelines?
  • How far do you think the FAIR principles can be applied beyond research data?

Bring your thoughts about these articles to the community discussions next week.

Create

Time estimate: 15 minutes

Scenario: You’ve been entrusted with providing guidance to your institution in data citation. You want to show examples from trusted data repositories or metadata aggregators to model good data citation practices.

First, read this page on data citation: https://ardc.edu.au/resources/working-with-data/citation-identifiers/data-citation/

Then, choose from the following list of services and select examples of data citations for either a dataset, a collection, research software, protocol or workflow, even training examples!