Research categorization and the value of structured data
As the global scholarly record grows in volume and complexity, the risks of incomplete or weakly structured data become more pronounced ? particularly for benchmarking, evaluation and policy decisions.
Informed by decades of methodological development at the Institute for Scientific Information, this report examines how deliberate data curation, stable categorization and rich metadata underpin the Web of Science database and its ability to support credible discovery, evaluation and analysis.
Understand why clean, consistently structured research activity data is essential for credible benchmarking, evaluation and trend analysis.
Learn how differences in research culture, collaboration patterns and the impact of time on citations can distort analysis ? and how robust data categorization addresses them.
Explore how structured research data can be aligned with national research assessment frameworks and global objectives such as the UN Sustainable Development Goals.
See what can go wrong in search, discovery and analysis when effective structured research data is incomplete or missing ? from distorted collaboration indicators to misleading comparisons and unstable trends.
