tools-only Adding Taxonomy to CSV Workflow Diagram
Chapter: 07 - Taxonomy Data Formats Generator: mermaid-generator Match Score: 94/100 Difficulty: Medium
Specification
Purpose: Show the step-by-step process of adding taxonomy information to an existing learning graph CSV
Visual style: Flowchart with process rectangles and decision diamonds
Steps:
1. Start: "Learning Graph CSV without TaxonomyID"
Hover text: "Existing CSV with ConceptID, ConceptLabel, Dependencies columns only"
2. Process: "Identify Natural Categories"
Hover text: "Review all concept labels and group by topic, domain, or complexity"
3. Process: "Design TaxonomyID Abbreviations"
Hover text: "Create 3-5 letter codes (FOUND, BASIC, ARCH, etc.)"
4. Decision: "Use automated categorization?"
Hover text: "Choose between manual assignment or add-taxonomy.py script"
5a. Process: "Run add-taxonomy.py" (if automated)
Hover text: "Script uses keyword matching to suggest categories"
5b. Process: "Manually add TaxonomyID column" (if manual)
Hover text: "Insert column in spreadsheet, assign each concept"
6. Process: "Review and adjust assignments"
Hover text: "Check that categorization makes logical sense"
7. Process: "Run taxonomy-distribution.py"
Hover text: "Validate that no category exceeds 30% of concepts"
8. Decision: "Distribution balanced?"
Hover text: "Check quality report for over/under-representation"
9a. Process: "Adjust categories" (if unbalanced)
Hover text: "Merge over-represented categories or expand under-represented"
→ Loop back to step 6
9b. End: "Learning Graph with Taxonomy" (if balanced)
Hover text: "CSV ready for JSON conversion and visualization"
Color coding:
- Blue: Data processing steps
- Yellow: Decision points
- Green: Quality validation
- Orange: Manual review steps
Swimlanes: Not applicable (single-actor process)
Implementation: SVG flowchart with hover tooltips