Crossref XML Generator

Download, edit, and convert metadata for DOI registration.

A web-based tool for metadata librarians to manage Crossref submissions without navigating complex XML schemas or APIs. Pull existing DOI metadata, modify it in a spreadsheet, and generate valid Crossref 5.3.1 XML for submission.

Use Cases

Who uses this:

• Metadata librarians managing institutional repositories
• Journal managers updating DOI records
• Repository administrators maintaining publisher metadata

Common workflows:

• Bulk ORCID enrichment — Download 500 article records, add author ORCIDs in Excel, resubmit to Crossref
• ROR affiliation updates — Pull existing metadata, append ROR identifiers to institutional affiliations, generate updated XML
• Metadata corrections — Fix author names, affiliations, or publication dates across multiple DOIs without manual XML editing
• New DOI registration — Create CSV from local records, add required Crossref fields, generate submission XML

Why CSV as intermediate format:

• Editable in Excel, Google Sheets, or any spreadsheet tool
• Supports bulk find-and-replace operations across hundreds of records
• No XML syntax knowledge required for metadata staff
• Version control friendly for tracking changes

Requirements

• Python 3.10+
• Dependencies: see requirements.txt

Setup

# Create and activate virtual environment
python3 -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run the application
python app.py

Open http://localhost:5000 in your browser.

Running Tests

pytest

Usage

Web Interface

1. Download — Enter a DOI prefix to pull existing metadata from Crossref
   • Choose to download all records or filter to most recent (100, 500, 1000, or custom limit)
2. Edit — Open the CSV in Excel/Sheets, filter to records needing updates, add ORCIDs, fix affiliations
3. Convert — Upload edited CSV to generate Crossref XML
4. Submit — Upload the XML to Crossref for DOI registration or updates

Library

from crossref_xml import download_prefix, generate_xml
import pandas as pd

# Download existing metadata
df = download_prefix('10.1234', email='you@example.org')
df.to_csv('my-dois.csv', index=False)

# Or download only most recent 500 records
df = download_prefix('10.1234', email='you@example.org', limit=500)
df.to_csv('my-dois.csv', index=False)

# After editing...
df = pd.read_csv('my-dois-edited.csv')
xml = generate_xml(
    data=df,
    depositor_name='Library Name',
    depositor_email='library@example.org',
    registrant='Library Name',
    include_references=True
)

with open('crossref-update.xml', 'w') as f:
    f.write(xml)

CSV Format

Required Columns

Column	Description
doi	The DOI being registered
title	Article title
publication	Journal or series name
authors	Semicolon-delimited author list

Optional Columns

Column	Description
resource_url	Landing page URL
publication_date	ISO format: YYYY, YYYY-MM, or YYYY-MM-DD
volume	Volume number
issue	Issue number
pages	Page range (e.g., 1-45)
abstract	Article abstract
issn_print	Print ISSN
issn_electronic	Electronic ISSN
pdf_url	Direct PDF link (enables text mining)
references	JSON array of citations

Author Notation

Authors use Surname, Given format with optional bracketed metadata:

Chen, Maria ORCID[https://orcid.org/0000-0001-2345-6789] ORG[Riverside University] ROR[https://ror.org/abc123]

Multiple authors separated by semicolons:

Chen, Maria; Okonkwo, David ORG[Field Research Institute]

Multiple affiliations for one author:

Larsson, Erik ORG[Northern College; Marine Biology Center] ROR[https://ror.org/def456; https://ror.org/ghi789]

The download function automatically formats author data from Crossref in this notation.

References Format

References stored as a JSON array:

[
  {"key": "ref1", "DOI": "10.1234/cited.2020.001", "doi-asserted-by": "publisher"},
  {"key": "ref2", "unstructured": "Author, A. (2019). Title. Journal, 10(2), 45-67."}
]

See docs/csv-guide.md for detailed field documentation including transformation examples and edge cases.

API Reference

download_prefix(prefix, email=None, limit=None, sort_by='deposited') → DataFrame

Download works for a DOI prefix from Crossref API.

• prefix: DOI prefix (e.g., '10.1234')
• email: Optional contact email for Crossref polite pool (faster rate limits)
• limit: Optional maximum number of records to download (None = all records)
• sort_by: Field to sort by when limit is specified ('deposited', 'updated', 'indexed', 'published'). Defaults to 'deposited' for most recent records.

generate_xml(data, depositor_name, depositor_email, registrant, include_references=False, license_url=None) → str

Generate Crossref 5.3.1 XML from DataFrame.

• data: DataFrame with required columns
• depositor_name: Organization registering the DOIs
• depositor_email: Contact email for registration issues
• registrant: Registrant identifier (usually same as depositor_name)
• include_references: Include citation list in output
• license_url: Optional metadata license URL (e.g., Creative Commons license). If None, no license element is added.

validate_csv(df) → list

Check DataFrame for required columns. Returns list of error messages.

parse_contributors(authors_str) → list

Parse author string with bracket notation into structured data.

Validation

Before submitting to Crossref, validate your XML using the Crossref Metadata Parser. This catches schema errors and malformed data before submission.

Spot-check a few records manually against your source data—automated transformations can propagate errors silently across hundreds of records.

Limitations

• Maximum 500 records per XML batch (Crossref API limit)
• Journal articles only (no books, datasets, or conference papers)
• Generates XML for submission; does not submit directly to Crossref

License

CC0 1.0 Universal