Advancing Trustworthy Science through Evidence Synthesis, Responsible Research Assessment, Open Science, and Responsible AI

The rapid expansion of scientific literature, growing demands for research integrity, and the increasing integration of Artificial Intelligence (AI) are reshaping contemporary research and scholarly communication. This report reflects on a week-long interdisciplinary Faculty Development Programme that examined the convergence of evidence synthesis (systematic review and meta-analysis), bibliometrics, research evaluation, open science, innovation analytics, and responsible AI as complementary foundations of trustworthy science. Rather than viewing these domains as independent methodological traditions, the programme highlighted their evolving integration into a common framework that strengthens methodological rigor, transparency, reproducibility, accountability, and evidence-informed decision making. The discussions also emphasized the importance of structured methodological training in enabling researchers to critically evaluate emerging analytical tools, adopt AI responsibly, and apply robust evidence across diverse disciplinary contexts. The programme illustrates how integrated methodological capacity building can strengthen research integrity, responsible research assessment, and trustworthy knowledge production in increasingly AI-enabled research ecosystems.