Who benefits when, from FAIR data? Part 2 – Machines
AI and machine learning can be used to create more detailed, FAIR-er datasets to be consumed by the machines.
Topic
Academia
A collection of 5 issues
Who benefits when, from FAIR data? Part 1 – Researchers
We are optimistic of a future state world, where a group of researchers generates new information based on new hypotheses, for others to then pull together the combined world’s knowledge to look for new patterns and discoveries that the original authors had not thought to look for.
Halfway to happiness — what the OSTP update means in the grand scheme
As is the tradition in academic publishing, we can continue to stand on the shoulders of giants, specifically the decades of work done by early open access advocates and SPARC. The speed at which dissemination of research is improving itself is accelerating.
Academic Research Data. Is it being cited?
Obviously with the many different types of outputs that researchers want credit for, there are some that lend themselves to reuse and traditional citation metrics better than others.
Academic Data Curation: Who checks? Who Pays? How Much?
The research publishing system works. We get new drugs and new breakthrough discoveries every year. The goal of FAIR research data is to optimise this.