Many things you interact with everyday utilize metadata. Like filters on your favorite retail site, Netflix search results, and photo libraries. While this metadata provides descriptive information that makes things findable, it must be organized into a structure to be truly useful and scalable. That’s where metadata fields come in.
One simple way to understand metadata fields is to think about them in the context of a survey, which consists of questions and answers. The questions are essentially the metadata fields, and the answers are the corresponding data. Like survey fields, different types of metadata fields organize individual pieces of data.
What are metadata fields in digital asset management?
Metadata fields are input elements that are populated with data to describe things. In a digital asset management (DAM) system, different types of metadata fields answer questions about each asset. Including identifiers like: filename, photography type, description, and usage rights.
Metadata fields have a range of formats that allow DAM admins to capture and aggregate information that defines the assets being tagged.
Benefits of using metadata fields
A system of metadata fields is called a metadata schema. Building a schema with the appropriate fields helps ensure that metadata is accurate and complete, which improves the search experience by delivering the desired results.
Metadata field types
Our DAM system, the Widen Collective® offers admins 10 options for structuring each metadata field, depending on the desired input. Some are free text fields and others are controlled vocabulary fields.
Free text metadata fields allow users to enter information freely. There may be limits to the number of characters that can be entered, but users can enter any combination of letters and numbers. They work well for caption, product ID, and title fields.
Controlled vocabulary fields make users choose from a list of options, keeping metadata consistent across assets and users. When possible, use controlled fields. They work well for rights management, internal department, contributor, and location fields.
|Free text fields||Controlled vocabulary fields|
|Limited text field
(256 characters, single line, no carriage returns)
|Long text field
(32,000 characters, multi-line, carriage returns)
|Numeric field||Multi-select palette field|
(10,240 characters, multi-line, carriage returns)
(1,280 characters, single line, no carriage returns)
Each field type serves a different purpose. And while some of these fields are a better choice for creating consistency across the metadata values, it’s ultimately up to the DAM admin to determine which fields to use for their specific purposes.
Using free text fields
Text metadata fields allow the user to enter information in any combination of letters and numbers. Here is a brief overview of these text fields, and possible uses:
Numeric fields can only contain numbers, not letters or symbols. Examples could include Product ID or Job number.
Date fields allow users to enter metadata by selecting a date on a calendar, for things like Event date or Publishing date.
Limited text fields can contain a single line of 256 characters, and is appropriate for things like Asset title, Campaign, or Project manager.
Text fields allow up to 1,280 characters, and works well to capture a description in a Caption or a Keyword field.
Text areas and long text fields can be used for metadata that’s recorded in a paragraph format. These fields permit carriage returns and have a larger character limit (10,240 for text areas and 32,000 for long text fields). They could be used to import metadata from another source that lacks formatting, video transcripts, or complicated contractual metadata.
Using controlled vocabulary fields
Controlled vocabulary fields offer a range of benefits, and should be considered whenever possible. They can streamline the metadata entry process and improve metadata accuracy through reduced spelling errors. Further, these fields can be used as search filters.
Controlled vocabulary fields are comprised of standardized terms that often align with business terminology and needs. Best practices recommend that the terms should be listed alphabetically but there are exceptions depending on different use cases.
Here is an overview of the controlled vocabulary field options offered in the Collective:
Checkbox fields are ideal for a short list with multiple answers. Examples could include a list of brands, internal teams, or asset types (such as logo, presentation, final photo, b-roll video, etc.).
Dropdown fields are ideal when users need to select one option from a list. They could be used for a list of clients, vendors, or licensing terms.
Autocompleter fields look like text fields, but when the user begins typing they offer options from a controlled vocabulary list. This can be used when there is a very long list in which there is one answer.
Palette fields are good for long lists that can have multiple answers, such as a list of countries in which the asset can be used, or a list of products featured in the asset.
What about dependent fields?
Dependent fields are tied to another metadata field and are often used to capture more specific information about an asset. For example, global marketing teams often use dependent metadata fields to indicate which language is used. A dependent field is also known as a child field, and they are only visible when their related parent field is selected — which streamlines the metadata entry process. In the Collective, all parent fields must be a dropdown format.
Dependent fields can be helpful for a number of reasons, including rights management. The example below lists four options for a Rights management field. When the user selects one of these options from the dropdown menu, a new dependent (or child) metadata field is revealed to allow additional information to be entered. The child field can be any metadata field format. Here are a few examples.
- Unlimited use
Dependent field: text field to enter any relevant notes
- Limited rights
Dependent field: palette field to select the licensing source
- Editorial use
Dependent fields can also help manage complex keywording, that includes multiple sets of controlled fields. In the example below, a grocery store has a metadata field for Department, with a dropdown menu and accompanying dependent fields.
Dependent field: palette field with options like bread, bun, croissant, muffin, etc.
- Meat and seafood
Dependent field: palette field with options like beef, chicken, fish, shrimp, turkey, etc.
Dependent field: palette field with options like shredded, sliced, grated, etc.
- Packaged goods
Dependent field: palette field with options like snack, breakfast, baking, baby food, etc.
Dependent field: palette field with options like water, soda, juice, coffee, etc.
Streamlining metadata creation
There’s no doubt about it — effective digital asset management begins with strong metadata. But creating thorough and consistent metadata for each and every asset can be a laborious task. Fortunately, the Collective includes tools to help automate this process both upon upload and after assets are in the DAM system.
The Collective’s upload experience includes metadata tools such as upload profiles, metadata imports, and filename mapping, that enable users to add metadata to assets across all files or in subsets. Alerts can also be used to notify admins when metadata needs to be reviewed or added prior to being released.
When multiple existing assets require changes, batch editing allows users to update metadata for up to 500 assets within the DAM system. In addition to streamlined metadata entry and consistency, the ability to change metadata en masse comes in handy — especially when metadata fields change and values need to be updated or migrated to new fields.
The Collective offers auto-tagging powered by Clarifai artificial intelligence (AI). Out-of-the-box, the AI tags images with keywords. Custom training is also available to identify and tag keywords that are specific to your brands and products. Tools like this allow admins to spend less time tagging and more time on strategic work, like system optimization.
Metadata that works for you
Designing effective metadata fields for a DAM system is both an art and a science. But the good news is that the fields are not set in stone, and can be adjusted to reflect the evolving needs of your users. In fact, any effective DAM system optimization strategy should include periodic metadata field audits to ensure they still reflect how your users search for content. And if you need help developing a metadata schema — or retooling an existing one — Widen has metadata experts that are happy to help.
Note: This article was originally published in February 2017 and has been updated regularly to remain current.