Ghost in the MARC: Cataloguing the Synthetic Shift in Bibliographic Metadata

Metadata Standards MARC21 ONIX & Other Formats Best Practice AI & Future Tech

Generative AI is rewriting the rules of published content and catalogue workflows. Moving past the noise of speculative disruption, this guide examines actionable standards for ONIX and MARC21. Discover how to properly designate AI software as related works, attribute human prompters, and apply robust provenance tracking without compromising metadata integrity.

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2026-06-23

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In the shadowed neon stacks of the information age, where algorithms quietly forge new works and human creators still hold the line, clear provenance has never been more critical. How do we flag generative AI involvement in published content without descending into chaos?
This guide cuts through the noise for two key standards: ONIX for the book trade and MARC21 for library cataloguing. No fluff. Just steel.

// ONIX: Clear Standards for Publishers

EDItEUR, the body behind ONIX, has issued practical guidance in its Application Note: Aspects of AI in ONIX. Core rule: disclose AI use when it goes beyond de minimis assistance. Transparency serves retailers, platforms, and readers.

Key recommendations:

This approach is already influencing supply chains, with some platforms labelling or restricting AI-heavy content.

Primary source: Aspects of AI in ONIX (PDF) (EDItEUR, current as of 2026).

// MARC21: Provenance, Software, and Emerging Best Practices

Library systems move more deliberately, with a strong emphasis on metadata integrity. Groundbreaking practical guidance from the PCC Standing Committee on Standards (FAQ: Cataloging of Resources Generated Using Artificial Intelligence Software) has clarified how to handle synthetic contributions without breaking data structures.

Core elements & emerging practices:

OCLC’s Bibliographic Formats and Standards (BFAS) and the PCC Task Group on AI and Machine Learning reinforce these practices, balancing transparency with rigorous quality control.

Practical MARC21 Examples

To see how these principles translate into raw syntax, consider the following production-ready MARC21 bibliographic snippets aligned with the latest PCC and OCLC frameworks.

Example 1: Poetry Generated via Code-davinci-002

LDR  01050cam a2200289 i 4500
001  ocn987654321
245 00 $a I am code : $b an artificial intelligence speaks / $c poems by code-davinci-002 ; edited by Brent Katz, Josh Morgenthau, and Simon Rich.
500    $a The Code-davinci-002 program, developed by OpenAI, was used to generate the poetry.
655 _7 $a Computer poetry. $2 lcgft
700 1_ $a Katz, Brent, $e editor.
700 1_ $a Morgenthau, Josh, $e editor.
700 1_ $a Rich, Simon, $e editor.
730 0_ $i Related work: $a Code-davinci-002.

Example 2: Culinary Guide with Multi-Model AI Assistance

LDR  01120cam a2200313 i 4500
001  ocn123456789
100 1_ $a Wisniewski, Mike, $e creator.
245 12 $a A dash of AI : $b a journey through AI-generated cuisine : written using ChatGPT, illustrated using Stable Diffusion and DALL-E 2 / $c prompts and commentary by Mike Wisniewski.
730 0_ $i Related work: $a ChatGPT.
730 0_ $i Related work: $a DALL-E 2.
730 0_ $i Related work: $a Stable diffusion.

// TL;DR – Relevant Fields & Codes (Quick Reference)

ONIX

MARC21

Key Resources

// In Summary

ONIX offers ready-to-implement, market-oriented solutions – ideal for publishers and distributors. MARC21 focuses on precise, integrity-first cataloguing, providing nuanced frameworks for treating AI as a related work alongside human operators. In both realms, the rule is the same: Transparency builds trust in the age of the EU AI Act and beyond.
Standards evolve. Check the sources. The archives endure when the records stay honest.

Title Graphic: “Ghost in the MARC”
generated with Grok Imagine by Grok (xAI) in collaboration with the author

Citation

For attribution, please cite this work as

Schmalfuss (2026, June 23). OS DataMercs: Ghost in the MARC: Cataloguing the Synthetic Shift in Bibliographic Metadata. Retrieved from https://www.datamercs.net/posts/2026-07-23-ghost-in-the-marc-cataloguing-the-synthetic-shift-in-bibliographic-metadata/

BibTeX citation

@misc{ghost-in-the-marc-ai-cataloguing,
  author = {Schmalfuss, Olaf},
  title = {OS DataMercs: Ghost in the MARC: Cataloguing the Synthetic Shift in Bibliographic Metadata},
  url = {https://www.datamercs.net/posts/2026-07-23-ghost-in-the-marc-cataloguing-the-synthetic-shift-in-bibliographic-metadata/},
  year = {2026}
}