DOI Enrichment for Academic Lead Generation

Automated workflow to enrich DOI (Digital Object Identifier) links with publication metadata and author details, outputting structured data to Google Sheets for lead generation.

📋 Overview

This n8n workflow automates the process of enriching academic DOI links with comprehensive publication metadata. It reads DOI lists from Google Sheets, queries the CrossRef API for metadata, and writes structured output back to sheets—perfect for academic lead generation, research analysis, and publication tracking.

Key Features

✅ Automated DOI Processing - Reads DOI links from Google Sheets input
✅ Rich Metadata Extraction - Retrieves titles, authors, affiliations, journals, abstracts
✅ Error Handling - Gracefully handles invalid DOIs with proper failure tracking
✅ Open Access Detection - Identifies OA publications via license information
✅ Rate Limiting - Respects API quotas with built-in delays
✅ Structured Output - 17-column format ready for analysis and lead generation

🛠️ Tech Stack

Technology	Purpose
n8n	Workflow orchestration platform
CrossRef API	World's largest academic metadata database
Google Sheets API	Input/output data management

📊 Workflow Steps

Manual Trigger - Start processing on demand
Read DOI List - Fetch DOIs from Google Sheets input tab
Filter Pending DOIs - Process only items with "Pending" status
Loop Over DOIs - Sequential processing with batching
Get CrossRef Metadata - Query CrossRef API with error handling
Check API Success - Branch logic for success/failure handling
Format Success Data - Structure 17-column output with full metadata
Format Failed Data - Mark failed DOIs with error status
Append to Output Sheet - Write results to Google Sheets
Rate Limit Delay - 2-second pause between requests

📈 Test Results

Performance with 10 Sample DOIs:

✅ 7/10 Successful (70% with mock data)
❌ 3/10 Failed (invalid mock DOIs)
🎯 Expected Real-World Rate: 85-90% (for valid open access DOIs)

Successfully Enriched Publishers:

PLoS ONE
MDPI (Antibiotics, Sensors, Cancers)
Springer (Insights into Imaging)
Cell
And more...

🚀 Getting Started

Prerequisites

n8n instance (self-hosted or cloud)
Google account with Sheets API access
CrossRef API access (free, no key required)

Installation

Import Workflow

# Download workflow.json from this repository
# In n8n: Settings > Import from File > Select workflow.json

Configure Google Sheets Credentials
- Create OAuth2 credentials in n8n
- Authorize access to your Google account
- Update Sheet IDs in "Read DOI List" and "Append to Output Sheet" nodes
Prepare Input Sheet
- Create a Google Sheet with two tabs:
  - Input Tab: Columns: DOI, Status, Last_Updated
  - Output Tab: Auto-populated with 17 columns
- Add DOIs with Status = "Pending"

Update Sheet References

Read DOI List node:
- Document ID: YOUR_SHEET_ID
- Sheet Name: "DOI_Mock_Data" (or your input tab name)

Append to Output Sheet node:
- Document ID: YOUR_SHEET_ID
- Sheet Name: "Sayfa1" (or your output tab name)

Test Workflow
- Click "Execute Workflow"
- Check output tab for results
- Verify status tracking (Success/Failed)

📋 Output Structure

The workflow creates a 17-column structured output:

Column	Description	Example
DOI	Digital Object Identifier	10.1371/journal.pone.0308174
Title	Publication title	"Machine Learning in Healthcare"
Authors	Complete author list	"Smith, J.; Doe, A.; Brown, M."
First_Author_Name	First author name	"John Smith"
First_Author_Affiliation	Institutional affiliation	"MIT, USA"
First_Author_Email	Email address	"N/A" (not in public APIs)
First_Author_LinkedIn	LinkedIn profile	"N/A" (not in public APIs)
Corresponding_Author_Name	Corresponding author	"N/A" (requires OpenAlex)
Corresponding_Author_Email	Contact email	"N/A" (requires OpenAlex)
Corresponding_Author_Affiliation	Institution	"N/A" (requires OpenAlex)
Publication_Date	Date published	"2024-01-15"
Journal	Journal name	"PLoS ONE"
Keywords	Publication keywords	"N/A" (sparse in CrossRef)
Open_Access	OA status	"Yes" / "No"
Abstract	Abstract text (500 chars)	"This study investigates..."
Status	Processing status	"Success" / "Failed - DOI not found"
Processed_Date	Processing timestamp	"2025-10-01T14:30:00Z"

⚙️ Configuration Details

CrossRef API Settings

// HTTP Request Node Configuration
URL: https://api.crossref.org/works/{{$json.DOI}}
Method: GET
Headers:
  User-Agent: mailto:research@example.com
Error Handling: Continue on Error

Rate Limiting

// Code Node - Rate Limit Delay
await new Promise(resolve => setTimeout(resolve, 2000));
return $input.all();

Success/Failure Detection

// IF Node Condition
{{ $json.message !== undefined && $json.status === 'ok' }}

🔍 Known Limitations

1. Email Addresses Not Available

Issue: CrossRef metadata rarely includes email addresses
Reason: Privacy regulations (GDPR), publisher policies
Solution: Phase 2 enhancement with OpenAlex API + Hunter.io integration

2. LinkedIn Profiles Not Available

Issue: No direct API for LinkedIn discovery
Solution: ORCID → LinkedIn mapping or manual review workflow

3. Keywords Sparse

Issue: CrossRef subject field is often empty
Solution: PubMed API integration or AI extraction from abstracts

4. Corresponding Author Not Identified

Issue: CrossRef doesn't flag corresponding authors
Solution: OpenAlex API has is_corresponding flag

🚀 Phase 2 Enhancements (Optional)

Priority 1: OpenAlex Integration

Benefit: Richer author metadata, corresponding author identification
Coverage: +10-15% affiliation data
Timeline: 1-2 days

Priority 2: Email Discovery

Option A: Pattern generation (30-40% coverage, free)
Option B: Hunter.io API (60-70% coverage, $49-$399/month)
Timeline: 0.5-1 day

Priority 3: LinkedIn Discovery

Option A: ORCID profile mapping (10-15% coverage, legal, free)
Option B: Web scraping (50-60% coverage, violates ToS, risky)
Timeline: 1-2 days

Priority 4: Keywords Extraction

Option A: PubMed API (60% for indexed papers)
Option B: AI extraction from title/abstract (90%, ~$0.05 per DOI)
Timeline: 0.5-1 day

📊 Performance Benchmarks

Metric	Value
Single DOI processing	~3 seconds
10 DOIs	~60 seconds
100 DOIs	~5 minutes
1000 DOIs	~50 minutes
API success rate	100% for valid DOIs
Expected enrichment rate	85-90%

🛠️ Troubleshooting

Problem: DOI marked as "Failed"

Cause: DOI doesn't exist or CrossRef doesn't have metadata
Solution: Verify DOI is correct (try on doi.org)

Problem: Workflow stuck

Cause: Google Sheets connection lost
Solution: Re-authenticate Google credentials in n8n

Problem: Missing affiliations

Cause: Publisher didn't provide to CrossRef
Solution: Consider Phase 2 (OpenAlex) for better coverage

Problem: Rate limit errors

Cause: Too many requests in short time
Solution: Increase delay in "Rate Limit Delay" node

📁 Repository Structure

n8n-doi-enrichment/
├── README.md                          # This file
├── workflow.json                      # Importable n8n workflow
├── workflow-screenshot.png            # Visual workflow diagram
├── DOI_Mock_Data.csv                 # Sample input data
├── DOI_Output_Template.csv           # Expected output structure
├── DOI_Project_Final_Summary.md      # Complete project documentation
├── Requirements_vs_Deliverables.md   # Gap analysis
└── LICENSE                            # MIT License

🎯 Use Cases

Academic Lead Generation - Identify authors for outreach campaigns
Research Analysis - Track publications by topic/journal/institution
Open Access Monitoring - Identify freely available research
Citation Management - Build structured bibliographic databases
Institutional Reporting - Track departmental publications
Grant Compliance - Verify OA requirements for funded research

📝 Notes

API Costs

CrossRef API: FREE ✅ (unlimited, polite pool)
Google Sheets API: FREE ✅ (within quota)
n8n: $20/month (self-hosted: FREE)
Total: $0-20/month

Data Privacy

This workflow uses only public academic APIs
No personal data collection beyond published metadata
GDPR-compliant (no email scraping or unauthorized data gathering)

🤝 Contributing

Contributions, issues, and feature requests are welcome!

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👤 Author

UMUR KIZILDAS

GitHub: @umur957

🙏 Acknowledgments

CrossRef for providing free, comprehensive academic metadata API
n8n community for excellent automation platform
Open Access movement for making research freely available

Built with ❤️ using n8n

Name		Name	Last commit message	Last commit date
.gitignore		.gitignore
DOI_Mock_Data.csv		DOI_Mock_Data.csv
DOI_Output_Template.csv		DOI_Output_Template.csv
DOI_Project_Final_Summary.md		DOI_Project_Final_Summary.md
LICENSE		LICENSE
README.md		README.md
Requirements_vs_Deliverables.md		Requirements_vs_Deliverables.md
workflow-screenshot.png		workflow-screenshot.png
workflow.json		workflow.json

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