How ITS Research Intelligence Works
The platform separates institution identity, scholarly research metrics, trend calculations, quality gates and public rankings so users can see what each indicator does—and what it does not measure.
Institution identity
ROR is used as the canonical organization identity layer where available. OpenAlex supplies scholarly research metrics and links institutions back to ROR. Records are normalized before public use so alternate names and identifiers do not automatically become duplicate institutions.
Research Performance Score
The current overall score combines five-year publication output, five-year citations, h-index, i10-index and publication growth. Volume indicators are log-normalized before weighting so very large institutions do not dominate solely because of scale. The score is research-specific and does not claim to measure teaching quality, student satisfaction, employability, finances or reputation.
Momentum
Momentum emphasizes direction of travel. It uses recent publication and citation growth alongside current research scale. Growth values are bounded before scoring so a very small starting value cannot create an unrealistic advantage.
Public quality gate
An organization can exist in the database without becoming an indexable public page. University pages require an active education institution, country identity, substantial five-year output, multiple active research years, multiple topic signals and adequate data completeness. Country and field pages require minimum numbers of index-ready institutions. This is the core anti-thin-content rule.
Field intelligence
Field pages use OpenAlex topic classifications associated with institutions. The field score blends topic-signal volume, overall research performance and recent growth. It is not presented as a complete disciplinary ranking until deeper work-level field normalization is implemented and validated.
Updates and reproducibility
Scholarly metadata changes as affiliations, works and citations are corrected. ITS therefore records synchronization dates and treats rankings as dated analytical snapshots. The system never converts missing data into invented metrics.