You’ve heard of open data. But what is FAIR data?
Talking to Kate LeMay from the Australian Research Data Commons and Lambert Heller from the TIB Open Science Lab
The benefits of data sharing are well understood. Data sharing increases trust in the conclusions derived from the data. And it means that the data can be re-used — combined with other datasets and interrogated in new ways to answer new questions. Increasingly, the big breakthroughs in science are coming from data collected by one group of scientists and analysed by another group. But making data available in principle is not the same as making it available in practice.
This is where the FAIR (Findable, Accessible, Interoperable, Reusable) Guiding Principles come in. First proposed in 2016, FAIR has been championed by the major funding organisations (who want to see maximum return on the data collection they support) and data librarians (whose job is to look after scientific data). But it’s yet to achieve recognition amongst the people who really matter — the scientists who produce the data.
And so for my latest article for Nature Index, I spoke to two FAIR experts, Kate LeMay from the Australian Research Data Commons and Lambert Heller from the TIB Open Science Lab. You can read the article here.