When dealing with large collections of digital marketing content—images, videos, documents, and brand assets —two important concepts that are essential to keeping it all organized and accessible within a DAM solution are metadata and taxonomy.
While the two terms can sometime be confused, the best way to think about these two driving forces into a DAM’s structure is as follows:
Metadata is ‘data about data,’ or better known as keyword tags on files.
Taxonomy is the organizational structure of your data. Think of taxonomy as the filing cabinet that arranges and connects your content or in digital asset management terms, as folders or categories.
Let’s take a deeper look at the definitions, examples and benefits of both Metadata and Taxonomy and how each of these are used to best structure a digital asset management system.
What Is Metadata?
At its core, metadata is the information that describes and gives context to digital files, making them easier to find, share, and use effectively across teams and platforms. In the world of AI and machine learning, metadata is also critical as content enriched with metadata enables AI systems to more accurately process, and analyze data reducing errors in results.
When we implement a digital asset management system for a brand large or small, we often talk about metadata as being the “attributes” or “tags” that describe files. Files can be any type of digital file, for example: a document, video, audio, excel, image or even a creative file format such as InDesign or Photoshop.
Here is a sample list of all files supported within a digital asset management software platform.
What are the Benefits of Metadata?
With compounding digital content, searchability of content has never been more important. When implemented correctly when setting up or maintaining your DAM, metadata can yield many obvious benefits to your team.
- Metadata Makes finding files faster, significantly reducing wasted time searching for files.
- Metadata helps avoid content duplication. Marketing teams spend 30-40% of budgets on content creation and production. If the assets can’t be found easily, some content might be recreated and duplicated.
Metadata protects talent usage rights and avoids fines. Copyright information embedded in metadata helps to ensure everyone abides by how the files were meant to be used. Review dates embedded in assets and in your DAM can alert you to when files are due to expire and can advise where they are being used.
What Types of Metadata Exist?
There are many types of metadata that you can use to make creative and digital assets more easily accessible. These include descriptive metadata, inherited metadata, embedded metadata, structured metadata, administrative metadata and custom metadata.
1. Descriptive Metadata: describes the content of a digital asset, and includes keyword tags and the description of a file. For example, an image of a girl in a blue car could have the following keywords associated: ‘blue’ ‘car’ ‘vehicle’ ‘girl’ ‘beach’. Often, these keyword tags can be automatically generated with AI. The description of the file could be: Girl in a blue car by the beach.
2. Inherited Metadata: is automatically associated with an asset based on its properties, like file format (ie JPEG or GIF), size, and dimensions. This type of metadata is generally automatically extracted when you upload the file to your digital asset management software.
3. Embedded Metadata: Embedded metadata can also be included with an asset, such as EXIF data in images. EXIF metadata contains technical information about an image such as camera settings, date and time when the photo was taken, aperture, ISO and shutter speed settings and GPS location data.
4. Structured Metadata: This is a crucial type that allows you to create a custom taxonomy for organizing assets in your DAM. An example is categories or filters applied to an asset that creates a structure. Custom filters are a great way to help you search across common themes such as geographies, media types (tv, radio, print), or even customer segments without needing to use additional folder structures.
5. Administrative Metadata: Administrative metadata helps DAM Administrators to manage the asset, including information about its creation, format, expiration dates and usage rights.
6. Custom Metadata: There will also be attributes you would like to assign your content that is bespoke to your business. Custom metadata fields are things you want to track to make digital content more interoperable with other systems (such as a website or a PIM), and are typically SKU’s or product codes, campaign, cost, project or job numbers. Here is an example of a custom metadata upload field.
What are Examples of Metadata?
When we think about opportunities to apply metadata to a digital asset, there are several fields that are available as standard in the DAM, and of course you can create your own metadata fields.
Examples of Metadata:
- Title: “Receptionist at a Desk”
- Author: “John Smith”
- Date Created: “March 15, 2025”
- Keywords: “man, worker, receptionist, office, young, smiling, happy, desk, telephone”
- Usage Rights: “Internal only”
- File Type: “JPEG”
You can have structured metadata (ie a pick list) or unstructured metadata (open-text fields). This data can be added manually or generated automatically (uploading to the DAM, the metadata is automatically extracted from the file and the asset is tagged with AI).
Metadata and AI Automation in Digital Asset Management
Digital asset management solutions were some of the first MarTech systems to include AI as a standard feature, specifically to assist digital asset management librarians and administrators to manage metadata tagging at scale. As there are so many parameters to consider when tagging digital assets, using AI to automate the bulk of content tagging, is a way to ensure it gets done every time an asset is uploaded, and for the most part, it is done in a comprehensive way. The following are ways that AI is used for metadata management in DAM software:
- AI Automatic Keyword Tagging for Image Files
- General Keywords:
Auto-tags for General Keywords are automatically detected from recognizable objects, living beings, scenery, and actions that appear in images. - Objects:
Auto-tags for Objects are automatically detected from objects or living things identified in the image. - Brands:
Auto-tags for Brands are automatically detected from commercial brands in the image. To note this only includes brands that are trained within the AI model. - Landmarks:
Auto-tags for Landmarks are automatically detected from identified landmarks in the image, such as the Eifel Tower, Times Square, London, and the Golden Gate Bridge.
- General Keywords:
- AI Automatic Keyword Tagging for Audio and Video Files
- Audiovisual Keywords: Auto-tags for Audiovisual Keywords are detected from insights on the different keywords discussed in media files. These keywords are detected from the speech and visual text and automatically tagged against the asset.
- Topics: Auto-tags for Topics are automatically inferred, based on various keywords from the speech and visual text.
- Objects: Auto-tags for Objects are automatically detected from visual objects and actions displayed.
- Locations: Auto-tags for Locations are automatically detected from the speech and visual text.
- Brands: Auto-tags for Brands are automatically detected from the speech and visual text. To note this only includes brands that are trained within the AI model.
- AI Facial Recognition for Images
AI powered Facial Recognition technology seamlessly integrates with IntelligenceBank, enhancing user capabilities to swiftly identify and tag individuals within images. During the digital asset upload process, the system automatically assigns a name or corporate ID number (tag) to individuals in the images.Additionally, a dedicated Training Center is available to facilitate the training of faces for recognition purposes.
Facial recognition tagging in digital asset management is critical for managing talent usage rights within a digital media library, and also locating images of staff and customers when they want to be extracted from the DAM library.
- AI Automatic Keyword Tagging for Image Files
What is digital asset management taxonomy?
Taxonomy is the hierarchical framework to organize content. Ultimately it defines how metadata values (like tags) will relate to each other and will determine how files are grouped together.
Think of taxonomy as the “filing cabinet” that arranges and connects your content. Examples of Taxonomy are best thought about as folder structures.
Such as:
- Region > Europe > Germany
- Media Type > Video > Online Product Tours
- Products > Lighting > Wall Lights
Ultimately, taxonomy helps users navigate and filter through content in a logical manner and drill down into categories.
When you are implementing a digital asset management system for your business, getting the taxonomy structure right for your digital asset library is a critical step in the process, as it directly affects both searchability of the assets as well as usability of the digital asset management system.
Best Practice Digital Asset Management Taxonomy
When you are building a digital asset management taxonomy, there are several best practices to optimize usability of your folder structure.
- User Journeys: It’s critical to understand how your end users search for and use their content, and importantly, how they name and categorize both folders and files – especially when you are implementing a new DAM or a global DAM – you want to work as closely as possible to how they are currently working – just better and more consistently.
- Audit Digital Content: Assess your creative content, stock libraries, video assets, and brand assets, and understand what’s there and what should go into the DAM, vs what should be in remote file cold storage (accessable but only to main admins and select individuals). We often advise people to ‘draw a line in the sand’ and only include the the digital assets that are being used actively. This audit will help inform the taxonomy structure of your DAM.
- Identify Commonly Used Terms: Think through your corporate marketing language in terms of how you call things and other commonly used terms. IE are trade shows called events, exhibitions, expos, field marketing or all of the above. Use the most commonly used terms for things, and use metadata tagging to ‘catch’ the other ways to which content is often referred.
- Create a Folder Structure: Now that you’ve figured out the major themes of your digital assets, it’s time to structure the data in a logical, hierarchical structure. While some companies opt for a flat file structure that only relies on metadata hierarchies, many teams find it easier to view files in folders. A trap some teams may fall into is making their taxonomies too deep, and not letting their metadata tags do the heavy lifting. The result is folder structures that are more than 4 or 5 levels deep, which can sometimes limit usability. Instead, decide which groups will be at the top level, such as: Campaigns, Stock Assets, Video, Brand Assets, Product Assets, and then use subfolders to categorize assets further.
- Standardize Naming Conventions: A consistent naming structure ensures that files and folders are easily recognizable by everyone who uses your DAM.
Best Practice Digital Asset Management Taxonomy
A well-structured taxonomy in digital asset management (DAM) brings alot of value to end users of a DAM system, especially when brand compliance and consistency are critical. Here are some key benefits:
- Faster Search & Retrieval: Taxonomy helps users find the correct digital assets quickly by organizing content in a logical, consistent way.
- Improved Consistency: Taxonomy enforces consistency across all assets, which is critical when multiple teams (or even external partners) are accessing the same DAM.
- Better Governance & Compliance: For industries with strict marketing regulations, taxonomy helps ensure the right assets are used correctly. You can apply permissions to control versions, rights usage, expiry dates, and approvals on the folder level, and some organizations use metadata tags to apply permissions on metadata tags.
- A Cleaner UX: When the structure of your digital asset library is more intuitive, it’s easier to use – for current team members, or new staff who are onboarding.
- Caters for Scale: As your digital content grows over time, a robust taxonomy ensures the digital asset management system can scale without becoming chaotic. This is critical for global brands or when acquisitions are made.
- Powers Personalization & Automation: Taxonomies are critical to power marketing automation and personalized content delivery such as: API’s calling digital assets for headless DAM applications; AI applications for personalized content creation and other automated workflows.
In conclusion, building a strong metadata and taxonomy framework and capability is essential for any business who is serious about optimizing the value of their digital assets. While the best practices and examples mentioned above are the ideal starting points when implementing DAM software, like any software solution, a DAM system is like a garden and needs to evolve and maintain as a business grows and develops over time. As such, to ensure metadata and taxonomy structures stay relevant to the business and the content managed within the DAM, at minimum annual audits and user feedback is essential, not to mention, regular analysis of DAM analytics and advanced reporting to see quantitatively how the DAM is actually being used.
