Digital Science launches AI-powered profile curation for Symplectic Elements
Digital Science has introduced a new suite of AI-powered capabilities for its Symplectic Elements research information management platform, designed to simplify and accelerate the creation and maintenance of faculty profiles.
The new feature, AI-Assisted Profile Curation, combines AI-Assisted Data Entry and a new beta capability, AI-Assisted CV Import, enabling institutions to convert CVs, documents and unstructured text into structured researcher profiles with significantly reduced manual effort.
The launch addresses a longstanding challenge for universities and research institutions, where maintaining accurate faculty profiles often requires substantial administrative input. Digital Science says some institutions report spending an average of 20 hours creating a complete profile for a single new faculty member.
The new workflow allows researchers and administrators to upload a CV, document or plain text, with AI automatically extracting and organising relevant metadata. Users then review and confirm the results before any information is saved.
According to Digital Science, the capability is built directly into Symplectic Elements and requires no additional integrations for hosted customers. The system maps extracted information to existing institutional metadata schemas, including custom fields and item types, while enhanced matching and deduplication checks help prevent duplicate records entering the system.
The platform supports a broad range of academic activities, including publications, grants, teaching, committee service and professional contributions. Digital Science says this is particularly valuable for disciplines such as Arts and Humanities, where outputs are often not captured through traditional automated harvesting systems.
Katy Krieger, Director of Faculty Personnel and Policy at the University of Oregon, said: “University of Oregon’s experience using the AI-assisted entry tool has helped us implement the system quickly at the university, has particularly supported the data collection for faculty in our professional schools, and has encouraged faculty and administrator buy-in. Our faculty provide their activity information in the system quickly and in a more standardiaed and readable manner, which means we are then able to use it for all of our major faculty reviews.”
Human review remains central to the process, with users required to approve all extracted information before it is added to a profile.
Jonathan Breeze, Executive Vice President of Academic at Digital Science, said: “AI-Assisted Profile Curation is the latest way we are helping researchers and administrators effortlessly populate Elements profiles. It offers customers (both new and existing) an innovative way to onboard new users of Elements with minimal manual effort, across every discipline and we’re excited to see how our customers choose to adopt this latest feature.”