In my previous post Web of information vs DAM, DM, CM, KM silos, I asked: “When a photographer’s phone number changes, will you update it in your DAM system? How many places will you have to update it in the DAM – is it stored in a single place, or has it been copied into each photo?”
DAM systems have traditionally focused on files and their metadata. With the metadata only existing in the context of the asset, not as standalone data in its own right. I’ve long been convinced that this is wrong, so it makes me very happy to see a trend in the right direction. A few quotes:
David Diamond – A DAM is no place for an “image”: “With content-focused DAM, you think in terms of, for example, of the words in yesterday’s press release. You don’t think in terms of the press release’s Word and PDF files as being separate entities. They are merely disposable containers for the content. And it is the content that needs metadata, not the files. It is the content that has a lifecycle, not the files. One of the many advantages of the Adaptive Metadata technology that Picturepark developed […], is that metadata can be abstracted from the assets themselves. This means, for example, the metadata can exist entirely on the asset class definition. Those assets assigned to the class inherit the metadata while they remain assigned.”
Louis King in a comment on the LinkedIn DAM group discussion on Why Images Don’t Belong In Your DAM (requires registration): “Each of these chunks of metadata represent investments that provide value to the asset. By separating them into individual but related assets DAM users are not burdened by the complexity of the whole but are focused only on the metadata that is returning value to their role. Very few DAMS do this but trends in metadata are moving rapidly in this direction. Take a look at Open Linked Data to see how that might play out in emerging DAM.”
Ralph Windsor – Digital Asset Management And The Politics Of Metadata Integration: “There are many other [applications] and you could include any system where the key entity is not an asset […]. In these scenarios, the external entity which contains the data of interest has an adjacent or perpendicular relationship with a digital asset. In other words, it is not above or below it in terms of the metadata schema hierarchy and needs to be treated independently (i.e. linked by association rather than part of the same record). […] The staff HR record and the employee photo are independent of each other and different users have to work on them separately from each other to fulfil independent business functions.”
I also like how Rory Brown quotes Douglas McCabe on Twitter: “Content has to be atomised because no one knows what the 4th wave of disruption will be (after desktop, phone, tablet)”
For a nice real-world example, see the BBC News Labs presentation on Storylines, Topics & Tags. Their News Archive doesn’t just store “article” and “image” assets, but also contains a database of people (with properties like “birth place”, “birth date”, “role”), organizations, places, events, themes (“unemployment”), and storylines (“the death of Nelson Mandela”). Each of which can be linked to the assets.
Once we agree on the need for standalone data in the DAM (or linked to the DAM) – asset-independent databases or knowledge bases – the next questions are how to model it, and how to ensure a good user experience. I think Topic Maps are perfect for modeling arbitrary, flexibly structured data. How are you doing it?
And what DAM systems do already have this functionality? I know of Picturepark with its Adaptive Metadata, ImageSnippets and our own DC-X with its Topic Maps engine. Any others?
Update: See also Eric Barroca’s (of Nuxeo) Deep Content: A Fresh Take on Content Modeling: “Deep content is about reversing that, putting (meta)data first, then crafting your content model based on your business domain.”
Update: I’m giving an example – newspaper articles about crime cases – in DAM Champ: Tim Strehle, Part 2.
Update: Demian Hess on Capturing DAM Relationships: “Because these systems pull together information from across the enterprise, they can support operations as varied as DAM, PIM, CRM, MRM and CMS. These systems provide "asset intelligence," with the understanding that anything can be an asset: an image, a piece of content, a character, a product, a contract or a user.”
Update (2016-11-17): In the Semantic / Graph DataBases and the evolution of Digital Asset Management webinar recording, Wendy Skoulding, Rich Carroll and Bill Covington explain how graph databases enable rich, flexible and highly related information modeling – and demo these features in Censhare.
Update (2017-03-31): In a preview of the Picturepark Content Platform [PDF]: “Build multi-node metadata and content relationship models that not only describe content, but provide semantic meaning and context, and ultimately improve the findability of specific content and the exploration of related content.”
Update (2017-04-05): Laurence Hart in Information Governance, Moving on from Content: “Information First: Here’s the deal. Content never stands alone. Yes it has metadata but there are entities that need to be managed that may not have content.”
Update (2017-04-11): censhare partner IO Integration – How a Semantic Network Makes the Unattainable Attainable: “Most digital systems require you to ingest your assets, which need to be some sort of digital file. A semantic network allows you to include simply metadata, which then relates to every relatable asset within the system. The difference is that anything can be an asset. A person and their project are both assets, meaning the project, the assets related to it and the person who needs them most are all related.”
Update (2017-04-18): I think your company needs its own Knowledge Graph.