For over a year, I have been working as a content engineer. It is not an entirely new role for me; I have worked on similar or related tasks in the past. But it is the first time I have concentrated on the trio of content, metadata, and semantics in the preparation, management, and use of content. It is also the first time I have approached my work as a content engineer.

And that is significant, as content incurs particular challenges, and content engineering brings particular practices to bear on those challenges.

What is content engineering? Or why does content need engineering?

Content—whether text, image, audio, video, or other medium of communication—is complex, varied. It is the raw stuff, the “contents”, of the media we create and publish. The books we write. The podcasts we record. The websites we develop.

Our interactions with content are mediated by technology. We use various tools to create content: platforms for authoring, designing, managing. We use various tools to publish content: printers, websites, mobile apps, chat bots, voice-assistants.

But significant challenges emerge for content in the context of technology. Consider, for instance, how content is moved between the many different tools for creating and publishing content. All too often, it is a manual matter of copying, pasting, reformatting, reconfiguring.

These are not altogether new challenges. They began to emerge not long after computers were first tasked with handling content: different publishing systems had different typesetting requirements, requiring different markup for the content to be rendered on each respective system. Content could not be readily moved and used on different publishing systems, as a result. [1]

SGML, the Standard Generalized Markup Language, was developed in response. It provided markup for describing the structure of the content, i.e. what the content is comprised of and how it is organized. [1] Significantly, this markup was independent of any one publishing system and its typesetting requirements. With the content independently explicated and encoded, it could be transformed for rendering in different publishing systems.

Today, the challenges for content in the context of technology are similar—but amplified. We have more and more varied tools in which we create content. We have more and more varied tools in which we publish content. And many of these tools rely on different forms and formats for the content. Somehow, the content needs to move from one tool to another: from authoring tools, to design and layout tools, to various publishing tools or channels.

And each delivery channel may require a markedly different configuration and presentation of the content. The same content—a particular recipe, for instance—may be published to a cooking website, a printed cookbook, and a voice-assistant answer. The content of the recipe is the same, but the form and format need to be adapted, transformed.

In addition, some are eager to tailor their content for specific contexts. For example, variations of content may be prepared for users based on their geographic location, audience segment, previous actions, presumed intentions. Different content may be delivered to different users, as a result.

Manual maneuvers to moving content between different systems, preparing content for different channels, and varying content for different contexts are time-consuming and error-prone. The solution, in keeping with the tradition introduced with SGML, focuses on the content—to ensure it can be used in the myriad systems, channels, and contexts required.

This problem set is the focus of content engineering.

What does a content engineer do?

A content engineer develops and implements solutions for content in the context of technology. We consider how the content should be structured, encoded, enriched, and supported to ensure it can be used as needed.

For instance, in my role as a content engineer, my tasks typically include:

• Modelling content to capture the structure of the content, such that, it can accommodate different systems, different channels, different contexts.
• Defining metadata to identify and describe critical aspects of the content for the systems or functions the content needs to interact with.
• Designing semantic models—i.e. taxonomies, ontologies, thesauri—to control terms and coordinate concepts populated in content and metadata.
• Identifying tools and specifying procedures to support the preparation and management of the content in day-to-day practice.

Together, these tasks provide a blueprint for handling content in complex publishing environments. They identify a structure for the content and metadata that facilitates moving content between different systems. They provide mechanisms for preparing and managing content for publication on different channels, in different contexts. They specify a common semantic for describing the content, so that wherever the content goes it can be readily identified, manipulated, used. In short, the goal is to engineer the content, and associated tools and procedures, to ensure content can be readily created, managed, published.

But, significantly, content engineering emphasizes, not only what work is conducted, but how that work is conducted.

Engineering is not merely implicated; it is central to the definition of content engineering. In keeping with the discipline of engineering, content engineering leverages “precedents, standards, frameworks, measurement, testing, and state-of-the-art technologies” to inform a systematic approach to design and implementation. [2]

Content engineering draws from foundational work in the content industry, leveraging precedents, standards, frameworks, and technologies tried and tested in the preparation and management of content. For example, content standards like XML, a descendent of SGML, often support the articulation and application of content models.

Content engineering also draws from foundational work in other fields, including software engineering and library and information science—two fields with notable histories tackling interchange and coordination across disparate systems, functions, processes.

In drawing from these established corpi, and in designing and implementing solutions, content engineering strives to be measured, methodical. It strives to balance various aspects of the problem, including efficiency, usability, accessibility, affordability. It strives to test, iterate, validate to ensure that the solution meets the need and addresses any constraints.

But, most importantly, the practice of content engineering focuses on content. In addressing challenges with content in the context of technology, content engineering considers, not only the technology involved, but the content itself. Content engineering asks: how can the content be engineered to ensure it can be used as needed?

[1] Joe Gollner, The emergence of intelligent content: The evolution of open content standards and their significance. January 06, 2009.

[2] Joe Gollner, Term of the week: Content engineering. September 11, 2014.