Knowledge synthesis (KS), a set of literature review methods originally developed to enhance the quality of medical evidence, has been adopted by researchers in such diverse fields as education, economics and social policy. As KS continues to spread, new questions are arising on how to further adapt it to disciplines that are far removed from the health sciences. What happens, for example, when it is applied in a completely different field — engineering? In this article, we describe and analyze challenges and opportunities we encounter as engineering librarians supporting researchers undertaking KS projects, often for the first time. Through the lens of the commonly agreed-upon five-step KS process (planning, identifying, evaluating, collecting/combining data and summarizing/reporting), we examine issues such as the adequacy of engineering databases for KS and popular tools for KS information management. We also discuss how engineering librarians can support each other in guiding researchers on choosing a KS method, in constructing and maintaining rigorous searches that meet the needs of engineering researchers, and in ensuring that librarians receive recognition for our contributions. We conclude by considering a possible future landscape for engineering KS, by outlining recommendations for the development of our capacity to support this work and by offering some initial thoughts on the rapidly developing implications of artificial intelligence. By addressing challenges and proposing solutions, we hope to pave the way for the enhanced use of KS methods in engineering and increase librarian confidence to support this work.
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Mawhinney et al. (2026) studied this question.
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