Those familiar with digital asset management understand the value of accurate and complete metadata profiles. In short, if content does not include quality metadata, that content is as good as lost.

When you type a search term in a content system, you are asking the system to match that term to available metadata profiles. In fact, the actual content associated with the metadata profiles is rarely, if ever, considered in search operations. When content is of a type that contains text, such as documents, it can be helpful to consider that text in search operations; but in most cases, metadata matches are given priority because metadata can lead to more reasonable and expected search results.

There are a few reasons why metadata profiles are more valuable than content when it comes to search:

• Visual content, such as images or video, might contain no words
• Textual content can be too abstract or varied to provide meaningful search results
• Metadata profiles can be designed to improve search, or extend data found in the content

That last point is key. When designing metadata profiles, you can account for the ways in which you expect users to find content. By creating metadata fields and values for those purposes, you can provide textual content that is weighted more heavily in search results.

Consider the content you are now reading. If you already knew of this document and you were trying to find it in a content system, you might use words from the title, such as “routing content enterprise,” or something similar. But if you were looking to discover new content similar to this document, and you had no idea that this document existed, there is no guarantee that you would think to search for these terms.

Without knowing the title of a given document, you would likely search for terms you expected to be within the content. The problem with the terms routing, content and enterprise is that they are found within many documents. Worse, the documents that contain the terms might have little or nothing to do with routing content through the enterprise.

This is why metadata profiles are so important. They enable you to define the gist of a given piece of content, using terms users are likely to use.

For similar reasons, metadata is important to search results from third party search engines, such as Google. Though Google is primarily a content search engine, it does consider metadata that is associated with content in certain ways. This can be expected to become even more valuable over time because Google (the company) is a proponent of linked data, sometimes called semantic metadata.

Linked data can be thought of as connections to external information that help define a given object. For example, if Google were to see that a content item called, “The Smartest Little Phone” was linked to the topic “children’s books,” Google could surmise that the content was not about compact mobile devices.

Metadata can also provide historical information about content. Though this could, of course, include actual historic information about photos of ruins, and such, it also refers to the history of the content itself: When was it created? When was it last updated? When is it due for another update?

Historic metadata can also refer to licensing or the planning or production discussions mentioned previously.

The current status of content is also represented by metadata. Simple statuses, such as “In Draft” or “Approved for Use” can be used to let users know what they can and cannot use. But status values can also apply to considerations like popularity, regional interest and more.

Most commonly, metadata is used to describe content itself. An image contains a “flower” or it was taken during “daylight” or in the middle of “summer.”

Users typically think first of descriptive metadata when performing searches. But when faced with too many results for a given search operation, they start to think of options for refining those results. This is why the value of a complete and accurate metadata profile for each piece of content is so important.

Even better if the content system supports flexible metadata profiles. Picturepark content systems, for example, support a technology called Adaptive Metadata. The value of this is that each piece of content in a system can potentially have a totally unique metadata profile. While in practice, this is not usually the case; it is common for a Picturepark system to support many different profiles, depending on the types of content in use in that system.

For example, content related to an event might call for metadata values that are unique to that type of content:

• Event name
• Event date
• Event location
• Sponsoring department

It would make no sense to include metadata fields for these purposes on, say, your financial or product documents. Yet, in systems that do not support flexible metadata profiles, this is what you would have to do if you wanted to include this information on your headshots.

Adaptive Metadata also permits metadata profiles to change over time. This is valuable, for example, when using the technology to provide extra fields for production or review. When the fields are needed, they can be added by any permitted user. When they are no longer needed, they can be removed by any permitted user.

In making metadata profiles so flexible, users find Picturepark systems less complicated because they see on each piece of content only those metadata values that make sense.