This article details librarian roles in applying traditional information knowledge and skills while co-developing a Living Knowledge Literature Review System (LKS). Increasing literature volumes and timelines for evidence synthesis risk industry decisions being informed by outdated data. Living reviews and synthesis challenge these models but include processes which can be streamlined. The LKS semi-automates literature review processes in particular knowledge domains using a novel machine learning algorithm. The LKS aims to distinguish relevant from irrelevant search results from conventional library searches, delivering outputs to researchers for summarisation and dissemination via a community targeted, purpose-built living evidence online portal (SEED POD). LKS screening accuracy is continuously improved through researcher and end-user feedback to create a more precise, semi-automated, living literature review system. Working closely with development teams and researchers in Social Early Emotional Development (SEED), librarians applied traditional information and searching knowledge into a new automation context, assisting in research question refinement, literature search development and licencing advice to build and optimise LKS functioning. Librarian input was highly valued in LKS production and optimisation. Including librarians in projects concerning automated evidence synthesis can enhance outcomes and lead to continued consultation and collaboration.
Stored only when both papers are in the corpus — 22 citations exist upstream.
Imported from OpenAlex (CC0) — nothing here is generated.