In the first part of this series, we looked at adaptive content and intelligent content. Our next ports of call are content engineering and content modeling. Anchors aweigh!
Content Engineering. Does It Hurt?
If content strategy is the planning, commissioning, rulemaking, repurposing, and publishing of content experiences and assets, then content engineering is the enabling, forming, structuring, organizing, and displaying of it, regardless of the channel. Like a feng shui tech warrior, if you like.
To really understand content engineering, we need to strip it down to its component molecules. They are: model, metadata, markup, schema, and taxonomy. Now, pull yourself up a comfortable chair, plump up your cushions, and enjoy this easy to understand definition of those very terms.
This is the process of creating content models that describe structured content. This means going beyond the confines of a sitemap or getting bogged down by page types. Instead, it is about understanding content types and their semantic relationship between each other.
This set of data provides useful information about other data to help applications, authors, robots, etc. understand how they can use and relate the content. It is an effective way to include low-level details that can deliver consistency and enhance how content is delivered to audiences.
Markup is intended to define and outline in order to offer a semantic structure for contents so it can be understood, enriched, consumed, indicated, transformed, and reused.
This form of metadata provides meaning and relationships to content. Often involving published standard vocabularies, like schema.org, in order to describe concepts with standardized terms. Schema is used by robots for them to understand and relate ideas.
This maps concepts that are related and applies it to the content, frequently as tags. It enables dynamic content item collections to show the relationships between content. Taxonomy is important because of the features it supports and enables, such as navigation, personalization, reuse of related content, and search.
The value of content engineering is immeasurable. An optimized flow of content is achievable through a structured, discrete, and adaptive format, which in turn results in both explicit and implicit content personalization across multiple channels and devices. This forms an essential part of artificial intelligence, SEO, cognitive computing, and machine learning.
Content Modeling—the Ultimate Food Chain
OK, so we have touched a little on the modeling part when talking about content engineering, now it’s time to dive in a little deeper.
If we look at content modeling as a food chain, it makes more sense. Content is there to be consumed, otherwise, it is a pretty pointless exercise creating it in the first place. In an ideally pragmatic world, everybody would be getting the content they want, understanding it correctly, and not missing out on any important parts that are absent.
We can think of it as tailoring your conversation in culturally diverse environments with differing levels of noise. Ordering a drink in a posh restaurant is a very different experience to ordering one in a noisy nightclub. The outcome should be the same, but the process and delivery of that content request are very different. Likewise, with content modeling, it is possible, based on the channel and context, to deliver your message in a clear and appropriate manner by ensuring that channel receives the content in a format that complies with both the viewing and technical capabilities/limitations of that channel.
Content modeling allows you to take all the elements of your content types within a project, apply detailed definitions to them, and outline the relationships between them. Providing such information gives developers the info necessary to structure their approach so they can deliver the results desired and meet the needs of the people responsible for producing the content.
From the content producers’ perspective, the content model gives them the definitions they need to produce the content itself. It helps them be productive because it removes unnecessary steps, is consistent and intuitive, and easy to use.
The content model consists of three main components, they are:
- The assembly model
This is how content producers take the raw elements and assemble them to make the final content output, such as webpages, newsletters, etc.
- Content types
The way in which content can be defined as a unique type based on its distinctive configuration.
- Content attributes
Defining the elements, both metadata and content, making up each type. As well their relationship to each other.
I hope you have found this series useful. If you would like to share your experiences with the topics covered, please share them in the comments section.