A knowledge model is not just a fancy buzzword for a controlled vocabulary. It’s more complex than that. A knowledge model is more similar to a knowledge organization system, which I defined in an earlier blog post. As a system or a model, it comprises not only the concepts, their labels and attributes, and their relationships, but also rules or policies for their use. Furthermore, a knowledge model is either a complex type of knowledge organization system, such as a thesaurus or an ontology, or a set of multiple controlled vocabularies to be used in combination for the same content set that form a set of taxonomies, such as facets, but it is not a simple single controlled vocabulary. The designation of “model” is also what is used for RDF, SKOS, and OWL-based systems. These are often called semantic models.
Before they had dictionaries, John Donne wrote:
No Man is an Island No man is an Iland, intire of itselfe; every man is a peece of the Continent, a part of the maine; if a Clod bee washed away by the Sea, Europe is the lesse, as well as if a Promontorie were, as well as if a Manor of thy friends or of thine owne were; any mans death diminishes me, because I am involved in Mankinde; And therefore never send to know for whom the bell tolls; It tolls for thee. MEDITATION XVII: Devotions upon Emergent Occasions
The same is true for your DAM. It doesn’t just need the use and involvement of teams of users to influence its ongoing development, regular attention from a Librarian and a developer, and a manager to oversee it all. To realize its full potential, it needs to connect: connect to other systems, to have it’s role in a true workflow, to automate billing and tagging tasks, to be part of the PIM (Product Information Management) system. On this topic are two recent articles, one from cmswire, and the other, from Widen.
Graphics are always great, as a picture is worth a thousand words.
How DAM and PIM Streamline E-commerce by Nate Holmes speaks to how a proper DAM takes its place among the PIM, ERP, and end-site usage systems in a large organization, say one that has a websie full of products for sale. t discusses a case study with Harman, Inc. Crow-eating time: I scoffed in an earlier post at managing a billion assets, but have recently thought more about how a site like Amazon could approach this number of images when you look at variations in color and size n their inventory. It also discusses some of the differences between a PIM and a DAM, and why it is probably best to let each do its role.
On CMSWire, there’s an related, uncredited missive, Understanding the Value of a Connected Intelligent DAM, talking about how Marks & Spencer and the Smithsonian are using OpenText DAMs and AI to master their assets, and use them to “has fully automated processes to import and deliver thousands of assets daily to a variety of channels.”
Good food for thought when you consider what is next in your DAM journey.