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DITA: The Darwin Information Typing Architecture


Level 3: Specialization and Customization

With specialization, DITA can provide structural support for information typing strategies, improving authoring consistency and guiding quality improvements. Specialization can also model content more closely for particular subjects or types of deliverable, which can be leveraged by semantic search and customized processes.

Scenario

An insurance company team wants to author all their content in XML to take advantage of the conditional processing and multi-channel output. They create a domain specialization, as well as structural specializations for claims, and policies and procedures in order to handle the insurance-specific concepts. With all the content sourced in XML, they can automate their system to combine policy and procedure information with actual claim information to create just-in-time compound documents.

Investment

In this third level of adoption, you expand the information architecture to be a full content model, which explicitly defines the different types of content required to meet different author and audience needs, and specifies how to meet these needs using structured, typed content.

Organizations that use DITA benefit from the ability to specialize or evolve the standard to provide the structure and semantic control needed for their content model. They can create their own specialization or participate on the DITA Technical Committee and work with others to create industry or content-specific specializations. DITA specializations require resources, time, and expertise, but provide content structure standardization.

In addition to creating new structural standards, organizations may choose to customize transforms to provide customized output deliverables, such as training materials or data sheets.

In an industry where several companies work together and exchange content, it makes more sense to develop a common specialization that structures the content to meet industry-specific requirements than for a single organization to develop a specialization that applies only to their content. The benefits of working on a common specialization are that you can easily incorporate and re-brand content as well as share the resource burden for specialization development.

Return

By investing in a content model that differentiates between the needs of the content authors and deliverable consumers, you can truly customize the output deliverables to meet the needs of various audiences. The first step is to adopt specializations supported by the DITA Technical Committee (TC) to provide more structure for authors when creating common content types. By utilizing these specializations, you make it easier for authors to create consistent information and maintain a standards-based architecture that supports interchange with other teams or organizations.

The next step is to create specializations to meet the specific needs of your organization, industry, or users. There are different types of specializations:

  • Topic information type specializations, such as glossary or API reference, which provide a standard structure for authoring specific types of information.
  • Deliverable specializations, such as bookmap, which provide a consistent structure and metadata optimized for a particular deliverable type.
  • Domain-specific semantic and structural specialization, such as semiconductor design documents, learning materials, policy and procedure documents, and financial documents, which have standard structures within the procedure documents, and financial documents, which have standard structures within the domain or industry.

As more industries embrace standards for increased quality and reliability, specialization can provide structure for meeting the standards as well as provide a mechanism for thought leadership.

The following figure shows how task, concept, and reference topics are specialized from the main topic type and how you can specialize directly from the main topic type or from any of the other specializations.

[Click image to view at full size]
Figure 5: Specializations

Once you specialize to specify semantic values, you can customize the content processing to leverage additional semantics. For example, once an insurance company team has created specialized markup for the provider of a policy, they can quickly create summary tables of policy claims, arranged according to provider.

In addition to providing consistency and control for content authoring and publishing, you can initiate discipline-specific quality initiatives, such as task analysis for technical documents, or training or use case development for engineering.

These types of process maturity activities also include identifying all the stakeholders in the content creation and generation processes and providing appropriate, customized authoring and editing experiences for each stakeholder role. For example, if the team has a mix of professional content developers and subject matter experts that collaboratively author content, you can tailor the authoring environments to meet the team's various needs. For example, the subject matter experts may need a subset of the functionality required by the professional content creators. Creating more standard, well-formed information at this third level of adoption provides a basis for improving quality and consistency across the content set.

DITA Features Used

This adoption level uses the following DITA features:

  • Specialization for different authoring needs/audiences. Specialization allows you to extend or evolve the DITA specification to create domain-specific or structure-specific content types. You can apply specialization at both the topic and map levels.
  • Modular processing architecture for shared infrastructure. Even as specializations create new markup, they can continue sharing processing logic and applications with unspecialized or differently specialized content. DITA's processing architecture allows for easy extension and customization by adding, removing, or overriding specific modules in a processing chain.


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