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Data Exchange and Data Management: Designed as One

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Data Exchange and Data Management: Designed as One 1

In previous posts of mine, I expressed my preference for in using existing metadata standards over designing data structures from scratch (see Finding Inspiration (and Solutions) From Metadata Standards and Commercial Exploitation of Digital Assets). In those previous posts I focused primarily on the design benefits that metadata standards can bring to your DAM systems. In this post, I want to highlight a different benefit; the ability to better communicate with your business partners. The reason I selected this as a topic was because Forrester Research Inc. just released a study, which I found extremely compelling.

Forrester released a study earlier this year entitled “The Total Economic Impact Of The DDEX Standards” which was commissioned by Microgen. I have written about the DDEX Standards in the past because I think that standard has particularly well-designed data structures to capture the necessary information around business models, distribution methods and pricing for the monetization of digital assets in a global marketplace. Forrester’s research focused on how this standard could reduce costs associated with setting up content feeds and exchanging data with one’s business partners. The report highlighted the costs associated with 4 main areas;

The benefits outlined in the study were considerable over the use of proprietary standards.

It is through these exchanges, from which licensing revenue is generated. Many of my DAM systems designs specifically focus on combining the data management needs with the data exchange needs. If both can be achieved using common data models, there are significant benefits to both your DAM and your company. And it is not just reserved for your external communications. Utilizing industry standards for internal data exchange between departments has the same benefits.

Exchanging data between systems is a critical component to any DAM system and it is increasingly important as we continue to interconnect our data and content with both internal and external systems. For the past 10 years we have been seeing many industry verticals develop XML data standards as a means to ease the challenges of interfacing disparate systems and making them more compatible with each other. But many are realizing that tighter integrations are possible and needed as our organizations see greater value in mixing their proprietary data with other private and public data sources. Because of this, we are seeing these XML standards being semantically remodeled into a knowledge base, which can much more easily integrate with other semantically modeled knowledge bases. Together these separate semantic data sets can be combined to infer new knowledge.

This is a clear trend. Data management and data exchange are being viewed as one. It is important for the future of your DAM and your company that you don’t conceptually keep them separate.

 

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