Concept Tree Builder
Visualize and organize your research concepts with this intuitive hierarchical tree builder designed for researchers, students, and academics. Create multi-level concept maps with unlimited depth, establishing clear parent-child relationships between ideas, themes, and categories. Each concept can include a name, description, category, and color coding for visual organization. Perfect for developing theoretical frameworks, organizing literature review themes, mapping research variables, structuring dissertation chapters, and visualizing complex relationships. Features expandable/collapsible branches for easy navigation of large trees, inline editing for quick updates, and the ability to add children at any level. Export your concept tree as a text outline for papers, CSV for analysis, or JSON for backup and sharing. Includes powerful search and filtering by category, statistics dashboard showing tree depth and node count, and browser-based storage for automatic saving. Ideal for qualitative research organization, theoretical model development, and systematic concept mapping.
Key Features
- Create unlimited hierarchical levels
- Add, edit, delete, and duplicate nodes
- Parent-child relationship mapping
- Inline editing for quick updates
- Color coding with 8 preset colors
- Category organization and filtering
- Expandable/collapsible branches
- Search across all concepts
- Filter by category
- Add children to any node
- Duplicate concepts (without children)
- Statistics dashboard
- Tree depth tracking
- Export to text outline
- Export to CSV (flat structure)
- Export to JSON (full backup)
- Import from JSON to restore
- Save to browser local storage
- Category breakdown analysis
- No login required
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Frequently Asked Questions
What is a concept tree and how does it help research organization?
A concept tree is a hierarchical visual representation showing relationships between research concepts, themes, or ideas. It uses parent-child relationships to organize complex information into logical structures. Concept trees help researchers develop theoretical frameworks, organize literature review themes, map variable relationships, and structure dissertation chapters. The visual hierarchy makes patterns, gaps, and connections immediately apparent.
How is a concept tree different from a mind map?
Concept trees are hierarchical with clear parent-child relationships flowing top-down or left-right, emphasizing structure and levels. Mind maps radiate from a central concept with more flexible, associative connections. Concept trees are better for showing classification, taxonomy, and nested relationships (e.g., theoretical frameworks). Mind maps are better for brainstorming and free association. This tool creates structured concept trees ideal for academic organization.
How many levels should my concept tree have?
Most effective concept trees have 3-5 levels deep. Too shallow (1-2 levels) lacks nuance; too deep (7+ levels) becomes difficult to navigate and overly granular. Balance breadth (siblings at same level) with depth (levels of hierarchy). This tool supports unlimited levels but includes statistics showing tree depth to help you optimize structure for clarity and usability.