Digital Asset Reuse: Making Assets Work Harder with Metadata and Taxonomy

By Stephanie Lemieux (@stephlemieux) Jan 25, 2010 Comments

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With ever shrinking budgets, many organizations are finding digital asset reuse a growing organization imperative. Effective use of metadata and taxonomies in the context of a DAM solution can facilitate great reuse patterns. Here's a start down that path.

Digital assets are anything that is non-textual: photos, videos, flash animations — any kind of rich media. Wonderful as they are, they do present challenges for information managers.

One of the key problems with managing digital assets is that more often than not, the responsibility for creating assets is decentralized and siloed by channel or market. One group is working on email marketing, another on web commerce, and the eLearning team in Belgium has no visibility what the team in France is accomplishing. Further, there may be no common repository where assets are kept, meaning that content creators have to go running around chasing source files from colleagues and agencies.

To maximize impact of spend and gain efficiency in the asset creation process, digital assets need to be managed in a central hub — a digital asset management system (DAM). However, it isn’t as simple as buying a new DAM solution, uploading all your assets and flipping the “on” switch — there is much more to reuse than technology. And one of the key elements of any DAM project is a solid metadata and taxonomy framework.

[Editor's Note: For an introduction to DAM, see the article Digital Asset Management Defined.]

Describing Assets — Good Metadata is Essential

Digital assets are more challenging than textual content in that they are completely dependent on their associated metadata for searchability in any system.

While search engines deal with unstructured documents by indexing their full text, we don’t have that luxury with digital assets. We can’t tell what a video is about without some sort of textual descriptor. Untagged assets are virtually invisible to search engines, making metadata and taxonomy invaluable allies in asset reuse.

DAM metadata is a tricky business; there are so many angles to consider:

Different types of assets have different metadata requirements: Photos have orientation and resolution, whereas videos have running lengths and audio transcripts. Each type may also have associated standards.
Assets can be decomposed into many levels: Each level may require its own metadata. A website might contain a flash animation, which in turn might contain a graph, which might contain an image of a product, each of which need to be tagged separately and differently.
Rights are key: To reuse an asset, users need to be able to identify what license rights have been obtained, when they expire, what channels they apply to, what ways the asset can be used — all of which can be hard to track and keep up to date.
Everything is subjective: Images can be harder to tag consistently, given their inherent subjective nature and the ambiguity of language. Images can represent actual things or concepts, and both are highly dependent on interpretation. Does an image of a green and a red tomato represent the concept of variation? Or just the foundation of a good salsa? And what if I search for "tomato" and you search for "vegetables" — would we both find this asset?

With all this, it can often feel as though creating DAM metadata is as much work as creating the asset itself. However, detailed metadata defines the ability to share and search assets and is worth the effort.