RANKING METHODOLOGY

How ResearchRank calculates and displays rankings

Every rank is tied to a defined population, ranking basis and reproducible data source. Rank-based certificates are issued only when that context is available.

1. Data source and entity matching

ResearchRank reads scholarly metadata from OpenAlex through its API. Author, institution and publisher identifiers are used to reduce name ambiguity. Profile metrics include indexed works, citations, h-index and i10-index when supplied by the source.

2. Exact metric rank

For supported entity contexts, rank is calculated as one plus the number of entities in the same population with a strictly higher cited-by count. Researchers with equal cited-by counts therefore share the same competition rank. Country and institution filters are applied before the count.

3. Subject / topic rankings

For researchers, the strongest OpenAlex topics attached to the author profile are evaluated as independent citation-impact populations. Other subject hierarchy pages may use matched-work grouping where a direct entity filter is not available. The certificate always records the actual ranking basis used.

4. Percentile calculation

Percentile position = rank position ÷ evaluated population × 100. ResearchRank Top 1%, Top 2%, Top 3%, Top 5% and Top 10% labels are assigned only when the calculated position falls inside the relevant threshold.

5. Composite analytics score

Citation impact35%

h-index25%

Research output20%

i10-index10%

2-year mean citedness10%

The composite score is an analytical aid normalized within a candidate set. It is not silently substituted for the stated ranking basis.

6. Multiple ranking scopes

A researcher may simultaneously hold global, country, institution and subject/topic ranks. State/region and gender ranks are separate ResearchRank verified cohorts and are never inferred from names or other proxies.

7. Calculation audit trail

Competition rankrank = 1 + count(metric > researcher metric)

Tied metric values share the same rank. No random tie-breaking is used.

Percentile positionpercentile = rank / population × 100

The smallest qualifying threshold is used: ≤1% Top 1%, ≤2% Top 2%, ≤3% Top 3%, ≤5% Top 5%, ≤10% Top 10%.

Populationpopulation = OpenAlex meta.count after filters

The same country, institution or topic filter is applied to both the target rank and population count.

Profile certificatesrules = works / citations / h-index thresholds

These do not claim a percentile rank unless a valid rank population is available.

8. Duplicate-profile controls

Search results are de-duplicated by source identifier. For researcher profiles, ResearchRank additionally checks probable duplicates using ORCID, normalized name, shared last-known institution and similar output counts. Possible duplicates are shown for review but are not silently merged, because merging distinct researchers would corrupt ranking metrics.

9. Responsible interpretation

Open bibliographic data can contain coverage, affiliation and author-disambiguation limitations. ResearchRank therefore displays the ranking basis and verification data with each certificate. A calculation can be mathematically exact for the returned source population while the underlying scholarly metadata may still contain source-level errors.

DETAILED GUIDANCE

Detailed service guidance

ResearchRank separates source data, analytical calculations, eligibility, payment, issuance and permanent verification so each step can be understood independently.

How should this page be interpreted?

Source-linked scholarly metadata describes the profile; ResearchRank calculations add ranking and recognition context. Eligibility is assessed independently of payment, and the certificate registry records the issued recognition separately from the changing live profile.

What happens when research data changes?

Profiles and rankings may change when indexed works, citations, affiliations, topics, open-access status or source records refresh. An issued certificate preserves its issue-time evidence and context; the live research profile can continue to evolve.

How are certification and payment separated?

Eligibility is determined before payment. Payment cannot create, increase or improve eligibility. Online payment must be verified by the server before certificate release; approved manual transfers follow the same issuance controls.

How are rankings and recognition calculated?

Ranking pages identify their ranking basis and evaluated population. Percentile recognition uses the profile's eligible ranking position relative to that population. Composite indicators are analytical aids and do not silently replace the stated ranking basis.

How is customer information protected?

Contact and delivery information is used for order fulfilment, certificate access, fraud prevention and limited transactional reminders. Sensitive payment credentials are handled by secure gateway components rather than stored in ResearchRank.

How does permanent verification work?

Each issued certificate receives a unique certificate number and verification record. Verification can show certificate status, issue date, recognition context and recorded scholarly evidence. A QR/reference on the PDF can point back to that record.

What are the limitations of bibliographic data?

Open scholarly metadata can contain author disambiguation errors, affiliation gaps, duplicate records, incomplete coverage and field differences. Source identifiers and linked records should be reviewed when the result is used for formal assessment.

What is the difference between live data and issue-time evidence?

Live data is refreshed for discovery and analytics. Issue-time evidence is the snapshot/context attached to the certificate transaction. This distinction helps preserve what was recognised even when current metrics later change.

How should ResearchRank recognition be described?

Use the exact certificate title and ResearchRank recognition class shown on the verification record. Do not describe a ResearchRank certificate as an official award or endorsement from OpenAlex, ORCID, a university, publisher or another external data source unless that organisation separately confirms it.