Speaking the Same Language: Using Generative AI to Drive Discoverability within CRIS Profiles

Abstract

Artificial intelligence is increasingly shaping the way research information is surfaced, explored, and understood. Within Current Research Information Systems (CRIS), AI-driven approaches are opening new avenues for enhancing the discoverability and accessibility of research outputs.

In this session we will briefly overview the new AI-powered functionality introduced within Symplectic Elements and how it can be used to improve engagement with research within public profiles, making it easier for both specialists and non-specialists to assess the relevance of scholarly work at a glance. The move introduces AI-generated publication summaries, which offer concise, plain-language explanations of research outputs alongside key highlights and keywords. This opt-in functionality allows institutions to enhance the accessibility of their researchers’ work while ensuring that individual scholars retain control over how AI-generated content is displayed on their profiles. By automatically generating digestible research summaries, this feature helps users - including potential collaborators, journalists, and members of the public - quickly grasp the significance of scholarly work without requiring in-depth subject expertise.