FAIR Release Notes: 2.29.0

Summary

This release contains a minor bug fix and backend changes to enable the introduction of AI backed search in FAIR, see below for more details.

Upcoming items

FAIR currently uses Azure Cognitive Search. This largely depends on string similarity to return search results (i.e. if a user wants to discover datasets about Alzheimer’s disease, their search really must include the term “alzheimer’s”).

AI-backed Vector search provides users with a more powerful and intuitive search experience, it can match on:

• semantic or conceptual likeness (“dog” and “canine”, conceptually similar yet linguistically distinct)
• multilingual content (“dog” in English and “hund” in German)
• multiple content types (“dog” in plain text and a photograph of a dog in an image file)

In our context, this means that a user could return datasets on Alzheimer’s disease while using a more general, but semantically similar search term like “cognitive decline”.

Vector search will remained disabled by default on all hubs, but as it represents a potentially significant boost to our existing search capabilities, we will be running a trial on a small number of hubs in the near future.

If this is something you would like to know more about please contact your Customer Success Manager.