While the success of a centralised DAM System rests on many factors including User Interface, intuitiveness and its ability to deliver to multiple channels, its key success factor is its search ability

If you are acquainted with asset management you will no doubt agree with some or all of the above statement (and if you don’t, you should!). After all, the basic purpose of any DAM is to retrieve information in an intuitive and orderly fashion, as well as letting all users find and view that information.

How a DAM achieves this is via the search and navigation software as well as the data itself that is stored in the system. A DAM system boasting features such as faceted, federated and predictive search is useless if the data itself isn’t searchable!

It is important to highlight this issue when considering the mid to latter stages of a DAM project. Common roadblocks that crop up relate to the enrichment of assets in terms of metadata and taxonomy.

Whilst some of the onus can rest with the DAM system itself and the techniques to help with the enrichment process, there are other factors; you may have heard of the keywords Semantic Web and Ontologies.

Briefly, Semantic Web is a web of data. It refers to a web that is able to describe things in a format computers can understand. It’s not about how pages on the web link together but rather the relationship between the things on those pages. It allows computers to accomplish tasks on the web that would normally be too longwinded for people to do, such as finding and actioning information on the web. For example, reserving a book on a library website may seem like a simple process but there are a number of actions as a user, you wouldn’t see such as finding the book, telling the system its being taken off the shelf, putting it in your basket, updating your library card etc.

Ontology can be described as a data model that defines/represents a domain. It describes the objects within it and the relationships between each object. It’s often used in semantic web as a knowledge base for representing the world or part of it by describing, individuals, classes, attributes and relationships. If we refer back to the library book example, the ontology is what tells the basket that a book goes into it, or that a barcode belongs to a book and so forth.
Both of these are complex topics in their own right, but the key message here is that the responsibility of utilising these techniques lies with the person or team in charge of uploading assets. Often this is a Content Manager who ensures that all assets uploaded are enriched correctly before pushing them through a workflow to be approved. It is a case of the age-old proverb ‘you get out what you put in.’

The 2 questions leading on from here are:
1) How do I tag my assets in a way that allows users to find what they want?
2) How do I control the quality of assets entering the system?
The second question will be addressed in Part 2 of this blog post, but in response to the first issue, I have 3 simple words for you; Metadata, Keywords and Taxonomy. Let me explain…

Metadata and taxonomies are two very different concepts and can be very easy to confuse. Metadata is data about data; it describes the data. Filenames, file types, sizes, EXIF info on images, all of this refers to metadata. Thankfully modern DAM systems (including our own Unify based solutions) pick up metadata automatically. However, assuming the system allows it, everyone has the opportunity to record much further useful metadata data via uploads and data imports into a DAM. Often elaborate processes on suitable metadata structures are defined with the client during the implementation phase and I would strongly advise anyone to utilise this process to get off to a good start.

Taxonomy refers to the arrangement and/or classification of data. Taxonomy does not attempt to define your assets/content but rather organises it into hierarchical relationships. The main benefit is to enable searches and browsing for assets when you are not totally sure what you are looking for. Once again, the vocabulary used to define your taxonomy will be specific to your company and should be controlled to ensure that end users understand what they mean.

When devising your taxonomy for tagging data a few best practices should be considered:

• Your taxonomy should be media independent
• Focus on a specific use
• Have a logical hierarchy
• Make it descriptive enough to be easily understood by users in different divisions or departments
• Conform to published taxonomy standards when possible (for more info see http://www.taxonomywarehouse.com)
• Should not be redundant to other defined metadata
• Avoid acronyms or abbreviations where possible
• Avoid nesting more than 5 levels deep if possible

(For more info see: http://www.databasepublish.com/blog/taxonomy-vs-metadata)

Keywords and tagging are also extremely useful when enriching data. Often users attach custom words to assets/content that they will then use for searching. Keywords are a perfect way for capturing those custom words. The more keywords an asset has, the increased likelihood there is for it to be found by multiple users.

If you are still wondering, ‘really, how important is this all?’ Ask yourself what makes eBay and Amazon searches so successful? How is it possible to find what you’re looking for without knowing exactly what it was you were searching for?

The answer is to pay attention to the metadata, taxonomy and keywords you attach to your data. Take advantage and utilise all help and guidance from your DAM provider to analyse your assets and work alongside in developing a good set of attributes.

by Andre Hollist who works in Technical Sales at VYRE.