Digital Science adds AI profile automation to Elements platform
Digital Science has launched AI-Assisted Profile Curation for Symplectic Elements, its research information management platform. The new capability automatically extracts data from CVs and documents to populate faculty profiles, with human review required before information is saved.
The feature combines AI-Assisted Data Entry with a beta CV import tool. Researchers or administrators upload a document, the system extracts and organizes relevant metadata, and users confirm the results before the data enters the system.
Universities currently spend an average of 20 hours creating a complete profile for a single new faculty member, according to Digital Science. The automation addresses this bottleneck, particularly for disciplines like Arts and Humanities where traditional automated harvesting systems miss outputs.
The system maps extracted information to existing institutional metadata schemas, including custom fields and item types. Enhanced matching and deduplication checks prevent duplicate records from entering the system.
Symplectic Elements customers can access the capability directly within the platform with no additional integrations required for hosted instances. The system supports publications, grants, teaching, committee service, and professional contributions across all academic disciplines.
Katy Krieger, Director of Faculty Personnel and Policy at the University of Oregon, said the AI tool helped the institution implement the system quickly and improved data collection for faculty in professional schools. "Our faculty provide their activity information in the system quickly and in a more standardized and readable manner, which means we are then able to use it for all of our major faculty reviews," Krieger said.
Jonathan Breeze, Executive Vice President of Academic at Digital Science, said the feature offers customers "an innovative way to onboard new users of Elements with minimal manual effort, across every discipline."
For teams managing research information systems, understanding AI Agents & Automation can help evaluate how these tools fit institutional workflows.
Your membership also unlocks:
