Discovery Metrics
View counts indicating dataset visibility
Justification
View counts indicate dataset visibility. Make Data Count (Sloan Foundation) standardizes usage metrics following COUNTER standards. The R bucket intentionally measures outcomes — this separation is SHARE’s key innovation.
Practical Guide
Track views. Outcome metric that validates deposit-time effort.
View counts measure dataset visibility — how many people found your dataset. This is an outcome metric: you can't directly control views, but better metadata at deposit time predicts higher visibility. All Zenodo datasets have view counts, confirming this metric is universally available.
For Repositories
- Implement COUNTER-compliant view tracking
- Display view counts on dataset landing pages
- Report standardized usage metrics via Make Data Count
For Depositors
- Monitor your dataset's view count as a proxy for visibility
- If views are low, revisit your description and keywords (deposit-time signals)
- Share your dataset link in publications and social media to increase discovery
Outcome metric — cannot be directly controlled at deposit time. Validates that deposit-time metadata quality predicts downstream visibility.
Standards Sources
Convergence score: 1/4 independent sources —
| Standard | Field / Property | Obligation Level |
|---|---|---|
| COUNTER Code of Practice | Dataset views | Standard |
| Make Data Count | Standardized usage metrics | Standard |
FAIR Principle Alignment
Primary mapping: Outcome metric (not FAIR-derived)
This is an outcome metric not derived from FAIR principles. The R (Reuse) bucket intentionally measures realized impact rather than metadata quality, enabling validation that deposit-time signals predict downstream use.
How This Signal Is Measured
Total unique views from repository analytics or DataCite Event Data. Binary for v1: any views = 1.
Empirical Evidence (Zenodo, n=1.3M)
Per-signal statistics use Zenodo as the primary validation source because it is the largest general-purpose repository with structured DataCite metadata, natural variance across all 25 signals, and available citation/usage data. Domain-specific repositories exhibit ceiling effects or restricted variance that preclude per-signal discrimination. Cross-repository validation is reported separately.
Prevalence
100%
of Zenodo datasets
Data Source
Zenodo (CERN)
1,328,100 records analyzed
Interpretation: Universal on Zenodo — all records have view counts. This is an outcome metric, not a deposit-time quality signal. Included to validate that deposit-time metadata quality predicts downstream visibility.
Quantitative Evidence
Scoring Formula
log₁₀(views + 1) × (4 / log₁₀(max_views))
Contribution: 4 of 100 points · Reuse bucket (0–20)
With Signal Present
1,328,100
datasets (100.0%)
μ = 0.244 citations/dataset
Without Signal
0
datasets (0.0%)
μ = 0 (baseline)
Method: N/A — universal prevalence · Source: Zenodo (n = 1,328,100)
Note: 100% prevalence. Outcome metric scored on continuous log scale (0–4 pts). Validates that deposit-time signals predict downstream visibility.
R — Reuse Bucket
All signals in this bucket: