Abstract Information management (IM) involves coordinating, utilizing, and controlling information within organizations. Over time, it has evolved to encompass various definitions and perspectives, reflecting its importance in organizational productivity, decision-making, success, and information enhancement. This study aims to comprehensively analyze the conceptual structure of information management and explore newly emerged and highly considered topics in theory and practice. By examining its core dimensions and multidimensional nature, the research seeks to uncover distinct clusters and main topics through the bibliometric analysis of keyword co-occurrence in related publications. The research data consists of 14,740 publications obtained from the Web of Science. The analysis is conducted using VOSviewer and biblioshiny, which are tools for bibliometric analysis. This study identifies five main sub-domains within information management: health information and technology management, big data management, research data management, data management systems, and information technology management. Trend analysis reveals the emergence of influential topics such as COVID-19, blockchain, smart contracts, artificial intelligence, and digital twins, reflecting the field’s rapid technological evolution. Citation analysis highlights that medical informatics, smart contracts, digital twins, and supply chain management are among the most impactful topics based on normalized citation rates. Furthermore, a notable thematic shift is observed from traditional information management practices toward more technical, systemic, and interdisciplinary approaches, particularly within health informatics and big data ecosystems. The findings underscore the dynamic and evolving nature of information management, emphasizing its increasing reliance on advanced technologies, the integration of diverse disciplinary perspectives, and the growing importance of ethical data governance frameworks. By mapping thematic clusters, this study offers valuable insights for researchers, scholars, managers, and decision-makers, helping them identify emerging trends, focus on key areas of interest, and plan future research directions. The findings also provide useful guidance for ontology engineers and developers of knowledge organization systems (KOSs), supporting the design and refinement of ontologies related to information management.