Picturepark’s Adaptive Metadata, which was released in 2013, was the first true innovation in Digital Asset Management that had been seen in many years. While other DAM vendors were focused on increasing the number of file types they supported, or adding another integration here or there, Picturepark recognized that metadata was the future of all content management, yet the way in we were managing metadata as an industry was too inflexible.
The problem with metadata traditionally is that it either has a fixed structure that is too rigid, or it has no structure, which leads to confusing search results and makes integration with other business systems difficult.

For example, systems that enable you to add tags are convenient and easy to use. But tags offer no context: Is it Apple the company or apple the English term for a type of fruit? When metadata becomes complex, context is required for efficient search.

Other DAMs provide metadata context through metadata field names. But these DAMs offer no way for that metadata field schema to adapt over time, based on the content of the digital asset or evolving business process circumstances. Sure, you can edit the database, but this means the schema changes for all assets, whether you want it to or not.

Say your DAM is integrated with your product information system. There are certain metadata values you’d want to have for the images used by your PIM, such as product name and number. Depending on the complexity of your product lines, you might have dozens of product-specific metadata fields. But the global addition of these fields to your DAM will cause confusion to users who are working only with PowerPoint presentations, employee headshots or other digital assets that are not directly related to your products.
Adaptive Metadata enables you to add all the product-specific metadata fields you need for those product images (in a single step), without affecting the metadata schemas on your other assets. Everything is simplified for users because the available metadata fields are always specific to and relevant for each asset.

In addition to adapting metadata to content, you can adapt metadata schemas based on status or other lifecycle circumstances. For example, assets in “Draft” status can have a set of fields that are used for the management of production assets, such as review comments or due dates. Once those assets are released, those production-related fields are removed and, perhaps, new fields are added.

While this might seem like unstructured metadata, it is not. Every field in Picturepark is a proper metadata field, so each has a field name and data type, and can optionally be assigned a controlled vocabulary to simplify and control user input. Adaptive Metadata is just a director of sorts that provides and takes away metadata fields at different points during the content lifecycle, based on policy and circumstances you define.

By avoiding the use of unstructured metadata to provide flexibility, Picturepark provides the search context users need, while it provides the consistent data structure required for reliable integrations with other business systems.

Adaptive Metadata is a standard feature of all Picturepark systems. If you’re interesting in learning more about how this technology can help you manage digital assets in a way that’s not possible with other DAM systems, please contact us.