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الأحد - الخميس: 06:30 صباحًا - 12:00 مُنتصف الليل
الجمعة: 05:00 مساءً - 12:00 مُنتصف الليل
السبت: 09:00 صباحًا - 12:00 مُنتصف الليل
المكتبات الأخرى
As the volume and complexity of global research outputs continue to grow, the way scholarly data is structured and categorized has become a strategic foundation for trustworthy discovery, evaluation, and decision making. Poorly structured or inconsistently categorized research data can lead to incomplete results, misleading analytics, and flawed comparisons, even when analyses appear technically sound. Based on insights from the Institute for Scientific Information (ISI) report “Research categorization and the value of structured data”, this webinar explores why rigorous data curation, stable classifications, and rich metadata are essential for meaningful research intelligence. We will examine concrete examples of how weak or incomplete data structures can distort citation analysis, benchmarking, collaboration indicators, and performance assessments, and how structured approaches such as subject normalization and time-aware metrics help mitigate these risks. Participants will gain a deeper understanding of how high-quality research data supports reliable search and discovery, enables fair and responsible analytics, and strengthens evidence-based decisions for institutions, funders, and policy makers. The session will also discuss practical implications for research evaluation frameworks, strategic planning, and the responsible use of metrics in a rapidly evolving scholarly ecosystem.
Language: English
Registeration Link
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