# Complete D4D Extraction Status - Four Input Cases

**Date**: 2025-11-08
**Status**: Approach 1 Complete ✅ | Approach 2 In Progress ⏳

---

## Four Input File Cases

### Case 1: Basic Individual Files
- **Input**: `downloads_by_column/` (22 files)
- **Description**: Individual downloads, 1 file per URL row, no tab scraping
- **Approach 1 Output**: `data/extracted_by_column/` - **16 YAML files** ✅
- **Approach 2 Output**: `data/extracted_claude_code/case1_basic_individual/` - **Pending** ❌

### Case 2: Enhanced Individual Files
- **Input**: `downloads_by_column_enhanced/` (90 files)
- **Description**: Multiple files per URL with tab scraping (Dataverse, FAIRhub, HealthDataNexus tabs)
- **Approach 1 Output**: `data/extracted_by_column_enhanced/` - **35 YAML files** ✅
- **Approach 2 Output**: `data/extracted_claude_code/case2_enhanced_individual/` - **Pending** ❌

### Case 3: Directory-Level Combined
- **Input**: `downloads_by_column_combined/` (3 files)
- **Description**: All basic files concatenated into ONE big file per PROJECT
  - `AI_READI_all_combined.txt`
  - `CM4AI_all_combined.txt`
  - `VOICE_all_combined.txt`
- **Approach 1 Output**: `data/extracted_by_column_directory_combined/` - **3 YAML files** ✅
- **Approach 2 Output**: `data/extracted_claude_code/case3_directory_combined/` - **Pending** ❌

### Case 4: Per-URL Combined (Tab Combined)
- **Input**: `downloads_by_column_enhanced_combined/` (6 files)
- **Description**: All tabs for each URL concatenated into ONE file per URL/row
  - AI_READI: 2 files (fairhub datasets with tabs combined)
  - CM4AI: 2 files (dataverse datasets with tabs combined)
  - VOICE: 2 files (healthnexus datasets with tabs combined)
- **Approach 1 Output**: `data/extracted_by_column_tab_combined/` - **3 YAML files** ✅
- **Approach 2 Output**: `data/extracted_claude_code/case4_tab_combined/` - **Pending** ❌

---

## Approach 1: Automated LLM API Agents 🤖

### Summary Status

| Case | Input Files | Output YAML | Status | Generator |
|------|-------------|-------------|--------|-----------|
| **Case 1** | 22 | 16 | ✅ Complete | validated_d4d_wrapper.py (GPT-5) |
| **Case 2** | 90 | 35 | ✅ Complete | validated_d4d_wrapper.py (GPT-5) |
| **Case 3** | 3 | 3 | ✅ Complete | validated_d4d_wrapper.py (GPT-5) |
| **Case 4** | 6 | 3 | ✅ Complete | validated_d4d_wrapper.py (GPT-5) |
| **TOTAL** | **121** | **57** | **✅ Complete** | **Automated batch processing** |

### Details by Case

#### Case 1: Basic Individual (16 YAML files)
- **Location**: `data/extracted_by_column/`
- **Projects**: AI_READI (4), CHORUS (1), CM4AI (4), VOICE (4)
- **Date**: Oct 16-30, 2025
- **Reports**:
  - `validated_d4d_processing_report.md`
  - `validated_d4d_processing_summary.json`

#### Case 2: Enhanced Individual (35 YAML files)
- **Location**: `data/extracted_by_column_enhanced/`
- **Projects**: AI_READI (5), CHORUS (2), CM4AI (12), VOICE (20)
- **Date**: Oct 31, 2025
- **Reports**:
  - `validated_d4d_processing_report.md`
  - `validated_d4d_processing_summary.json`
- **Notable**: Includes tab-scraped content from Dataverse, FAIRhub, HealthDataNexus

#### Case 3: Directory Combined (3 YAML files)
- **Location**: `data/extracted_by_column_directory_combined/`
- **Files**:
  - `AI_READI/AI_READI_all_combined_d4d.yaml`
  - `CM4AI/CM4AI_all_combined_d4d.yaml`
  - `VOICE/VOICE_all_combined_d4d.yaml`
- **Date**: Nov 1, 2025
- **Reports**:
  - `validated_d4d_processing_report.md`
  - `validated_d4d_processing_summary.json`

#### Case 4: Tab Combined (3 YAML files)
- **Location**: `data/extracted_by_column_tab_combined/`
- **Files**:
  - `AI_READI/fairhub_dataset_2_d4d.yaml`
  - `CM4AI/` (2 dataverse datasets)
  - `VOICE/` (healthnexus datasets)
- **Date**: Oct 31, 2025
- **Reports**:
  - `validated_d4d_processing_report.md`
  - `validated_d4d_processing_summary.json`

---

## Approach 2: Interactive Coding Agents 👨‍💻 (Claude Code)

### Summary Status

| Case | Input Files | Output YAML | Status | Generator |
|------|-------------|-------------|--------|-----------|
| **Case 1** | 22 | 0 | ❌ Pending | Claude Code (claude-sonnet-4-5) |
| **Case 2** | 90 | 0 | ❌ Pending | Claude Code (claude-sonnet-4-5) |
| **Case 3** | 3 | 0 | ❌ Pending | Claude Code (claude-sonnet-4-5) |
| **Case 4** | 6 | 0 | ❌ Pending | Claude Code (claude-sonnet-4-5) |
| **TOTAL** | **121** | **0** | **❌ Not Started** | **Interactive with human oversight** |

### Planned Directory Structure

```
data/extracted_claude_code/
├── case1_basic_individual/          # Case 1 results
│   ├── AI_READI/
│   ├── CHORUS/
│   ├── CM4AI/
│   └── VOICE/
├── case2_enhanced_individual/       # Case 2 results
│   ├── AI_READI/
│   ├── CHORUS/
│   ├── CM4AI/
│   └── VOICE/
├── case3_directory_combined/        # Case 3 results
│   ├── AI_READI_all_combined_d4d.yaml
│   ├── CM4AI_all_combined_d4d.yaml
│   └── VOICE_all_combined_d4d.yaml
└── case4_tab_combined/              # Case 4 results
    ├── AI_READI/
    ├── CM4AI/
    └── VOICE/
```

### Generation Metadata Template

All Approach 2 files should include:
```yaml
# D4D Metadata for: [Dataset Name]
# Source: [URL or file path]
# Input Case: [Case 1/2/3/4]
# Generated: [ISO 8601 timestamp]
# Generator: Claude Code (claude-sonnet-4-5)
# Method: Interactive extraction with human oversight
# Schema: https://raw.githubusercontent.com/monarch-initiative/ontogpt/main/src/ontogpt/templates/data_sheets_schema.yaml
# Reviewed by: [Name/email]
# Notes: [Any relevant notes about extraction process]
```

---

## Running Jobs

### Active
- D4D Agent (PID 33808): Processing `downloads_by_column_enhanced/` → `data/extracted_d4d_agent/enhanced/`
  - Status: Running (1h 20m)
  - Progress: 14/84 files (17%)
  - Note: This is a duplicate of Case 2 using different wrapper script

### Completed
- All Approach 1 extractions for Cases 1-4 ✅

---

## Next Steps

### 1. Complete Approach 2 Generation

For each of the four cases, generate D4D metadata using Claude Code:

#### Case 1: Basic Individual (Priority: Medium)
- Process 22 input files from `downloads_by_column/`
- Generate 16-22 D4D YAML files
- Output to `data/extracted_claude_code/case1_basic_individual/`

#### Case 2: Enhanced Individual (Priority: High)
- Process 90 input files from `downloads_by_column_enhanced/`
- Generate 35-90 D4D YAML files with tab content
- Output to `data/extracted_claude_code/case2_enhanced_individual/`

#### Case 3: Directory Combined (Priority: High)
- Process 3 large combined files from `downloads_by_column_combined/`
- Generate 3 comprehensive D4D YAML files
- Output to `data/extracted_claude_code/case3_directory_combined/`

#### Case 4: Tab Combined (Priority: Medium)
- Process 6 tab-combined files from `downloads_by_column_enhanced_combined/`
- Generate 6 D4D YAML files
- Output to `data/extracted_claude_code/case4_tab_combined/`

### 2. Comparison Analysis

After completing Approach 2:
- Compare quality/completeness between Approach 1 and 2
- Document differences in metadata richness
- Identify strengths of each approach
- Create recommendations for future use

### 3. Documentation

- Update CLAUDE.md with four-case documentation
- Create comparison report
- Document lessons learned

---

## Input File Statistics

| Input Source | Files | Size | Description |
|--------------|-------|------|-------------|
| downloads_by_column | 22 | ~10MB | Basic downloads, 1 per URL |
| downloads_by_column_enhanced | 90 | ~45MB | Enhanced with tab scraping |
| downloads_by_column_combined | 3 | ~25KB | All basic files combined per project |
| downloads_by_column_enhanced_combined | 6 | ~600KB | All tabs combined per URL |
| **TOTAL** | **121** | **~55MB** | **Complete input set** |

---

## Output File Statistics (Approach 1 Only)

| Output Location | YAML Files | Total Size |
|-----------------|------------|------------|
| extracted_by_column | 16 | ~50KB |
| extracted_by_column_enhanced | 35 | ~400KB |
| extracted_by_column_directory_combined | 3 | ~15KB |
| extracted_by_column_tab_combined | 3 | ~10KB |
| **TOTAL (Approach 1)** | **57** | **~475KB** |
| **TOTAL (Approach 2)** | **0** | **0KB** |

---

## Key Insights

1. **Case 2 (Enhanced Individual)** generates the most comprehensive metadata (35 files, 400KB)
2. **Tab scraping** (Case 2 & 4) captures significantly richer content than basic downloads
3. **Combined approaches** (Case 3 & 4) synthesize multiple sources into cohesive metadata
4. **Approach 1** is complete and provides automated batch processing baseline
5. **Approach 2** is needed to provide human-oversight quality comparison

---

**Last Updated**: 2025-11-08 20:27
**Next Action**: Begin Approach 2 generation starting with Case 3 (highest value/effort ratio)
