Data shapes library planning, research support, discovery, automation, and institutional decision-making. Bibliometric studies have treated analytics, research data management, artificial intelligence, metadata, and governance as separate or partially connected areas, leaving the wider structure of data-driven library and information services insufficiently defined. This study analyses 1,100 Scopus-indexed documents published from 2016 to 2025 through bibliometric performance analysis and science mapping. Results identify rapid publication growth, concentrated contributor patterns, and an intellectual structure linking information services, research data management, metadata, analytics, and artificial intelligence. Five frontiers organise the domain: AI-related service intelligence, analytics-driven service design, research data infrastructure, metadata and knowledge organisation, and responsible data capability. Citation analysis distinguishes wider citation visibility from library-specific intellectual anchoring. The study defines data-driven library and information services as an integrated socio-technical configuration organised through evidence use, data infrastructure, information structures, computational processes, and professional judgement. The synthesis supports comparative analysis of capability priorities across institutional and national settings.
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