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Can Semantics be the Peacemaker between ECM and DAM?

March 3, 2016 3 mins. read Jarred McGinnis

DAM, EMC, Gulliver and Lilliputians

It doesn’t help that Enterprise Content Management (ECM) and Digital Asset Management (DAM) are sometimes used interchangeably and often incorrectly. The world of DAM predates ECM. Digital Asset Management (DAM) is a collective term applied to the process of storing, cataloging, searching and delivering digital assets

DAM vs ECM

Digital Asset Management (DAM) systems centralize assets and establish a systematic approach to ingesting assets so they can be located more easily and used appropriately. ECM systems tend to be large-scale repositories of many types of content held across the entirety of an organization. An ECM will hold materials other than just digital assets such as operational documents and files.

An ECM central principle is to offer a single interface where employees can gain access to all of an organization's data. Share on X

Although, technically, an ECM can function as DAM, in practice most organizations and departments find they need a separate system as ECM tends to be too broad for anything but basic activities such as searching.

Added to this is a cultural divide of the practitioners not seen since Swift’s Lilliputians. Those close to the coalface of digital asset management find it hard to appreciate why they should care about all the other data across a vast organization when they have plenty to do managing the digital assets of their purview.

Those at the enterprise level who are concerned with the increasing demand for platform agnostic content pulled together in real-time that is 100% relevant for the consumer should be forgiven if they fail to appreciate the quirks and peccadillos of each and every data source across the organization.

Let’s not further complicate the picture by adding another acronym of Web Content Management (WCM) by considering content taken from 3rd party sources across the vast and changing world wide web.

Given this state of affairs, it is easy to understand why the battle continues as one side suggests an ECM (one system to rule them all) is fine and DAM practitioners point out the lack of optimization of ECM systems for certain content types and the lack support for functional requirements or specific business needs.

The Role of Semantics

The addition of semantic metadata represents content at a higher-level of abstraction enabling the creation of a programmatic approach to cross-departmental use of assets as content that more closely resembles how humans understand and use the content. It becomes the ‘lingua franca’ between the two opposing worldviews of DAM and ECM. Content is dealt with because of the people, places, organizations, brands, topics that it mentions rather than just structural metadata (e.g., file format, file size, creation date etc.)

The ability for systems to recognize automatically the topics and categorizations of content and the ability to infer context from that information enables different systems to treat content in dynamic ways. Concepts, entities, topics and categories are already useful fulcrums for moving content but it is just the start.

As an organization's understanding of semantics moves beyond faceted search, it can begin to leverage the relationships between concepts themselves and the content. Share on X

This has a number of benefits such as enabling contextually-aware search, improved automated tagging and dynamic digital products.

At the heart of the semantic approach is the concept of graph-driven databases such as GraphDB, which enables flexibility and responsiveness that traditional databases are incapable of. As the organization grows and changes or as the business need changes and grows so can the metadata model that is being used.

 

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Technical Author at Freelancer

Jarred McGinnis is a managing consultant in Semantic Technologies. Previously he was the Head of Research, Semantic Technologies, at the Press Association, investigating the role of technologies such as natural language processing and Linked Data in the news industry. Dr. McGinnis received his PhD in Informatics from the University of Edinburgh in 2006.

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