Structured authoring

The following is a list of pages on this site that are tagged with structured authoring.

Working with content references (conref)

Content referencing (conref) is a convenient DITA mechanism for reuse of content from other topics or maps. A fragment of content in one topic or map can be pulled by reference into any other topic or map where the content is allowed. To create the reference, start by creating an empty element of the type that you want to pull in, and then use the element's conref attribute to provide the target's location.

The architectural specification describes content referencing at:

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Working with maps

DITA maps collect and organize references to DITA topics to indicate the relationships among the topics. They can be used to identify the topics you want to include in a deliverable, and to create tables of contents and related links for the information.

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Writing DITA topics

DITA topics are the basic units of DITA content.

Topics are the basis for high-quality information. Each topic is organized around a single subject or answers a single question.

Each topic is typically authored as a unit. It consists of a title, which captures the subject of the topic, and further content.

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Topic-based authoring

Topic-based authoring has been a mainstay of technical information development since we first began developing help systems. We learned quickly enough that we couldn't split our existing books into help topics by making every heading level a new help page. Information originally designed with a narrative flow no longer made sense nor assisted users in finding exactly the content they needed. We had to rethink the type of information that our help systems should include and create a new set of standards for its development. The result is topic-based authoring.

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For some, perhaps the real question is Why XML? (or What is XML?), but assuming you have answered those questions (and are using XML), then the next step is to locate an appropriate data model for your content. This is an important step because you will spend a lot of time and money developing processes and selecting tools to support your chosen data model.

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