How does indexing differ from full-text search functionality in DITA?

November 10, 2023
|By Bryan Tipper

Indexing and full-text search functionality serve distinct roles in DITA documentation, offering different ways for users to find and access information. Understanding the differences between these two methods is crucial for designing effective documentation systems.

Indexing

Indexing in DITA involves the creation of an organized list of terms, concepts, or keywords that appear in the content. These terms, known as index entries, are typically curated by authors or subject matter experts to provide a structured and human-curated means of locating specific information within the documentation. Indexing relies on the identification and tagging of relevant terms in the content, which are then compiled into an index.

Full-Text Search

Full-text search functionality, on the other hand, allows users to perform keyword searches across the entire content of the documentation. This method doesn’t rely on pre-defined index entries but instead scans the entire text for matches with the user’s query. It provides a more flexible and comprehensive approach to finding information, as it can locate not only explicitly indexed terms but also related content based on the keywords used in the search query.

Differences in Implementation

In terms of implementation, indexing requires the manual creation and maintenance of index entries within the DITA content, while full-text search functionality typically relies on search engines or tools that automatically index and search the entire content. Indexing is well-suited for situations where specific terms or concepts need to be highlighted and organized for easy reference, while full-text search is valuable when users need to perform quick and broad searches to find relevant information.

Example:

Here’s an example of how indexing and full-text search functionality differ in DITA:


<index>
  <indexterm>
    <primary>Topic A</primary>
  </indexterm>
  <indexterm>
    <primary>Topic B</primary>
  </indexterm>
</index>

<topic id="topic_a">
  <title>Topic A</title>
  <body>
    <p>This is the content of Topic A.</p>
  </body>
</topic>

<topic id="topic_b">
  <title>Topic B</title>
  <body>
    <p>This is the content of Topic B.</p>
  </body>
</topic>

In this example, we have index entries for “Topic A” and “Topic B,” and the associated content for each topic. Indexing would allow users to find these topics directly by referring to the index, while full-text search functionality would enable users to search for keywords within the content of both topics, providing more comprehensive results.