--- title: "Video metadata standards: PBCore, EBU Core, and Dublin Core for MAM workflows" author: "Cutsio Team" date: "2026-05-25" lastmod: "2026-05-25" category: "Video Asset Management" excerpt: "Video metadata standards like PBCore, EBU Core, and Dublin Core provide frameworks for describing media assets in MAM systems. Cutsio's Visual Intelligence generates rich metadata automatically while supporting standard schemas." tags: ["Video Metadata","PBCore","EBU Core","Dublin Core","MAM Standards","Media Metadata"] --- ## What are video metadata standards? Video metadata standards are structured frameworks for describing video content in a consistent, interoperable way. Standards like PBCore (public broadcasting), EBU Core (broadcast), and Dublin Core (general digital assets) define which metadata fields should be captured, what values they can take, and how they should be formatted. Cutsio's [Visual Intelligence](/blog/visual-intelligence-for-video-teams-how-cutsio-understands-footage) generates rich metadata automatically — including transcripts, visual descriptions, and scene classifications — that maps to these standard schemas without requiring manual entry. ## Why do metadata standards matter for video workflows? Metadata standards matter because they ensure that video assets can be found, understood, and exchanged across different systems, teams, and organizations. A video file with standardized metadata can move from a production team's MAM to a broadcaster's playout system to an archive's preservation system without losing its descriptive context. Without standards, metadata is idiosyncratic. One editor might tag a clip as "INT. OFFICE — DAY — WS" while another tags the same clip as "Office wide shot daytime." Both are descriptive, but a search across the library must account for both conventions. Standards eliminate this ambiguity by defining a common vocabulary. Standards also enable automated metadata exchange. When a broadcaster receives video files from a production company, standardized metadata allows the receiving system to ingest the content with its descriptive information intact. Without standards, metadata must be re-entered at each transfer point. ## What are the major video metadata standards? Three metadata standards dominate the video production and broadcast landscape: PBCore, EBU Core, and Dublin Core. Dublin Core is the simplest and most widely adopted metadata standard. It defines fifteen core elements — title, creator, subject, description, publisher, contributor, date, type, format, identifier, source, language, relation, coverage, and rights. Dublin Core is a general-purpose standard that works for any digital asset, including video. PBCore is a metadata standard developed by public broadcasting organizations in the United States. It extends Dublin Core with video-specific fields including physical format, generation (original, master, copy), asset type (clip, program, series), and rights information specific to broadcast content. PBCore is the standard for public media archives and is increasingly adopted by academic libraries managing video collections. EBU Core is the metadata standard developed by the European Broadcasting Union. It is designed for broadcast production and archive workflows with fields for technical parameters (codec, bitrate, resolution), production context (program title, episode number, series), and rights management (territory, window, license type). EBU Core is the dominant standard in European broadcast organizations. | Standard | Domain | Video-Specific? | Key Elements | Typical Users | | :--- | :--- | :--- | :--- | :--- | | Dublin Core | General digital assets | No | 15 core elements | Libraries, museums, general DAM | | PBCore | Public broadcasting | Yes | Extends Dublin Core with broadcast fields | Public media, academic archives | | EBU Core | Broadcast production | Yes | Technical + production + rights metadata | European broadcasters | | Cutsio Visual Intelligence | Video production | Yes (automatic) | Visual, speech, scene, production attributes | All video teams | ## How does Cutsio's Visual Intelligence relate to metadata standards? Cutsio's Visual Intelligence generates metadata that maps naturally to standard schemas — but without requiring users to configure or enter any of it. Where a traditional MAM requires editors to fill in Dublin Core's "subject" field manually, Cutsio's Visual Intelligence generates subjects automatically by analyzing what appears in each frame and what is spoken in each segment. A clip of a customer testimonial about product pricing receives generated metadata including: visual descriptions (person, office environment, product on table), speech transcript (exact words spoken with timestamps), scene classification (interview, testimonial), and production attributes (medium shot, static camera, natural lighting). These generated fields map to Dublin Core's description and subject fields, PBCore's coverage and audience fields, and EBU Core's content description fields. For organizations that need to export metadata in standard formats, Cutsio's API provides access to generated metadata that can be mapped to any schema. The metadata is structured and consistent because it comes from automated analysis rather than human entry. ## What metadata should video teams capture? Video teams should capture metadata that makes content findable and usable. The most important metadata categories are administrative (who created it, when, for what purpose), technical (format, resolution, codec, duration), descriptive (what is in the content — subjects, people, places, events), and rights (who owns it, what usage is permitted). Cutsio captures descriptive metadata automatically. For administrative and rights metadata, teams can add context through Collection organization and file naming conventions. Technical metadata is captured from the source files during ingest. The metadata that matters most for findability is descriptive — and it is the category that teams most often fail to capture manually. Cutsio's Visual Intelligence solves this by generating rich descriptive metadata for every video without any manual effort. ## How do you implement metadata standards in a video production workflow? Implementing metadata standards in a video production workflow starts with identifying which standard aligns with your organization's domain and what level of metadata granularity your workflow requires. A corporate video team may need only Dublin Core's core elements. A public broadcaster requires PBCore compliance. A European broadcast facility requires EBU Core. With Cutsio, the implementation is simplified because the platform generates the most labor-intensive metadata — descriptive metadata — automatically. Teams configure which additional metadata fields they need for administrative and rights categories, and map Cutsio's generated output to their chosen standard. The key insight is that metadata standards should not drive workflow complexity. The standard should describe what already exists. Cutsio's automatic metadata generation provides the foundation. Teams add manual metadata only where their standard requires information that AI cannot derive, such as specific rights terms or production identifiers. ## FAQ ### Does Cutsio support PBCore metadata export? Cutsio generates metadata that maps to PBCore fields through its API. For organizations that need formal PBCore export, the API provides access to generated metadata that can be transformed into PBCore XML. ### What metadata does Cutsio generate automatically? Cutsio's Visual Intelligence generates visual descriptions, speech transcripts with timestamps, scene classifications, and production attributes for every uploaded video. This metadata is searchable within the platform and accessible through the API. ### Do I need to use a metadata standard if I use Cutsio? No. Cutsio's Visual Intelligence generates searchable metadata automatically without requiring users to configure or follow any standard. The standard compatibility is available through the API for organizations that need it. ### How does automatic metadata compare to manual metadata for search? Automatic metadata from Visual Intelligence is more comprehensive than typical manual metadata because it captures every visual element and spoken word. Manual metadata is limited by what the logger notices and has time to enter. Both are valuable, but automatic metadata ensures nothing is missed. ### What is the best metadata standard for a small video team? Dublin Core is the best starting point for small video teams because it is simple, widely supported, and covers the essential descriptive fields. As the team grows or enters a domain that requires more specific standards, metadata can be extended to match PBCore or EBU Core requirements.

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