DAM if you do and DAM if you don’t

How Digital Asset Management and identity management are perfect partners.

facial recognition - biometric security identification
Thinkstock

Digital Asset Management or DAM is traditionally associated with rich media and the companies who employ that type of content, such as media and entertainment. It is big business too. The market for DAM is expected to be worth $9.1 billion USD by 2024. Much of this is driven by the increasing importance of content marketing - digital content offering a very good ROI according to Smart Insights.

I’ve always felt that marketing is a discipline that can inform the world of digital identity. It is engaged with customers, it has a good grasp on user behavior, and it utilizes statistics and reporting to optimize systems. So, where does DAM fit into a consumer identity platform and how can digital content add benefit?

Identity + data = life history

Identity in 2018 is more than just identifying a person. Identity is also about the associated data, what the identity owner does with that data, and how that individual interacts with any third party that utilizes their data. Identity has become an overarching mechanism to communicate and perform transactions that are transforming literally everything that we do in our digital lives. Identity powers data and data powers identity – they are holistically and intrinsically linked. And, identity data takes many forms, from a simple piece of text to a video – literally, anything that can be associated with an individual can be part of their identity data. All of these snippets of information can be owned and tied to an individual (or a corporate) identity.

Also, importantly, that ownership, whether it be linked to an individual or an organizational identity, can be transferred, changed, and removed.

A digital identity can be used to confer ownership. What this effectively means is that asset-based content can become an identity attribute. The identity platform can be configured to associate an identity with a piece of content in the same way that it associates an identity with a name or address.  You can imagine, that as an identity profile matures, over time, it can build up large amounts of data that represent an individual or an organization’s life history.

DAM + IAM = iDAM

Identity-based digital asset management expands the use of attribute-based identity. Some more advanced DAM platforms also offer artificial intelligence and machine learning. The integration of AI-driven DAM platforms with identity services that offer identity verification has the ability to create a new system which I’ve termed identity-based DAM or iDAM.

In the iDAM system, rich media files, are associated with a verified identity. This identity can be an individual or could represent a corporate. Some example applications include:

  • Individual iDAM: Verification of an identity is increasingly using processes that need facial recognition or a video of the individual. These media are then also used to perform post identification services such as account recovery. Rich data like video can be associated with that individual and can be used and shared across multiple platforms – even to help perform verification on third-party systems. Workflow engines within DAM platforms can be used with the rich media to initiate transactions and services. The iDAM system being able to trace the access of the rich media by other services. The ability to weave rich media into a person’s digital identity opens up new usage models for identity and the data it is based on.
  • Corporate iDAM: Identity can also be associated with a group, not just an individual. Groups or even entire enterprises can be issued an identity which is then associated with individual pieces or entire libraries of rich media. DAM platforms integrated with an enterprise IAM using a RESTful API creates a powerful engine to distribute content across related services. It also offers a way to control access to these data and initiate workflow events.

The IoT and iDAM

The natural extension of iDAM is to include items within the Internet of Things (IoT). Associating an individual with an IoT device or object confers ownership; an example could be a connected car. The car details, including video history of services, images of collision damage, and so on, could all be stored in an iDAM system and associated with the owner using their verified identity. These details could be shared when making insurance claims, for example. When the car is sold on, the identity owner could record the transaction, and transfer ownership to the new owner using an online transaction driven by a verified identity. As part of this workflow, the iDAM platform would move all of the car history including any rich media, to the new owner – assigning them ownership along with the car. In other words, identity data-driven transactions including rich media to augment them are serviced using an iDAM system.

A healthy future for iDAM

The ultimate extension of iDAM will be within smart cities as digital identity is the life-blood of the smart city. Verified identity can be used within smart cities to connect individuals with other individuals and corporations. I wrote in a previous post on “Identity and the Smart City” that the digital assets of our day to day lives can be recorded and placed under our control at the point of generation of these data. Some of these data will be health data and will include items such as MRI scans, videos of scans, x-rays, and other rich media. The use of an integrated DAM system with identity management will allow smart cities and especially smart health to truly utilize health data in an intelligent and controlled manner. The control of that data use, and the consent to share and use such sensitive data, is inherent in the identity system.

As I said earlier in this article, marketers are often at the forefront of applying technology to consumer behavior. The time for a system comprised of DAM and identity to give us an iDAM platform is now. The application of artificial intelligence and machine learning to these services can only make it all the more powerful for our smart cities.

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