Understanding Your Tree Health and Data Quality Score
Learn how GEDminer evaluates your tree\'s data quality, what the health score means, and practical steps to improve your tree\'s completeness and accuracy.
What is the Tree Health Score?
The Tree Health Score is a composite metric showing overall data quality:
- 0-40: Needs significant improvement - many missing records and data issues
- 41-60: Fair - basic structure is present but many gaps remain
- 61-80: Good - solid foundation with room for improvement
- 81-100: Excellent - comprehensive data with few gaps
The score appears as a badge on the Overview dashboard and updates as you improve your data.
How the score is calculated
Multiple factors contribute to your score:
- Name completeness: Percentage of individuals with recorded names
- Birth date coverage: How many people have birth dates
- Birth place coverage: How many births have locations
- Death date coverage: Death dates for likely deceased individuals
- Death place coverage: Locations for recorded deaths
- Source citations: Percentage of facts backed by sources
- Error count: Number of detected data errors (reduces score)
- Warning count: Number of potential issues (minor score reduction)
Detailed quality breakdown
Click the health badge to see individual metrics:
- Names: What percentage of individuals have proper names (not "Unknown")
- Birth Dates: Coverage of birth date recording
- Birth Places: How many births include location data
- Death Dates: Death date completeness
- Death Places: Death location coverage
- Sourced: Percentage of individuals with at least one source citation
Each metric shows a progress bar so you can quickly see which areas need the most attention.
Improving your score
Practical steps to raise your Tree Health Score:
- Fix errors first: Use Integrity > Errors to resolve critical data issues
- Add missing dates: The Vital Sharpener shows which dates to prioritise
- Add locations: Even partial locations (country level) improve coverage
- Cite sources: Attach source references to verified facts
- Remove duplicates: Merge duplicate individuals to clean up the tree
- Fill census gaps: Use the Census Toolbox to find missing records
- Re-export and re-analyse: Check your progress after making improvements
Score vs. research quality
Keep in mind:
- A high score doesn't mean complete: There could still be missing ancestors or undiscovered branches
- A low score is normal for new trees: You have to start somewhere
- Some gaps are genuine: Records may not exist for all individuals
- Quality over quantity: A well-sourced tree of 500 people may be more valuable than an unsourced tree of 5,000
Use the score as a guide, not an absolute measure of your genealogy skills.