Metadata errors used to be manageable. Search engines were forgiving, and readers found content anyway. But now, researchers are exchanging database searches for AI-powered discovery, which surfaces content based on metadata quality. Journals with gaps and inconsistencies are at risk. The cost? Missed citations, lost readership, and compromised reputation.
Metadata quality sits across editorial, production, and technology, with no single owner, so the debt builds until it’s too expensive to ignore. Publishers tackling this aren’t starting from scratch. They’re assigning clear ownership and building remediation into existing workflows.
In this webinar, we’ll look at:
- What metadata debt is, and how AI discovery is changing what completeness means.
- What a realistic remediation program looks like for a mid-to-large journal portfolio.
- How to run a metadata audit, and the payoff for getting it right.
Speakers
Moderator
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