Embedded Indexing

A traditional index is created as a separate, stand-alone file from the book file(s). The indexer reads the book in the form of copy-edited laid-out galleys, either printed out or as a PDF on a computer screen, and creates the index entries in a dedicated indexing management software, from which a separate index file is generated and submitted to the publisher (often as RTF – rich text format), which gets converted and added to the end of the book’s file.

Embedded indexing, by contrast, involves creating an index in the same file as the book’s content, or via a connecting software tool to the book’s file, so that index entries not only appear in the compiled index but also link to tags or anchors within the book’s file at the location of the text passage that the index entry refers to. This can be done in various software tools: Word, desktop publishing software such as InDesign, XML, HTML, etc.

There are various benefits to embedded indexing:

  • Embedded indexing enables the creation and functioning of a hyperlinked index in an ebook.
  • Embedded indexing facilitates the reuse and modification of an index in a future edition of the book, saving time from creating a new index from scratch.
  • Embedded indexing shortens the book production process by enabling indexing on the unformatted manuscript prior to the laying out of the pages with formatting, as embedded index entries re-flow regardless of changes in page numbers.

While indexing professionals would hope the adoption of embedded indexing by publishers would result in more indexes in ebooks, this has not yet been fully realized. For the most part, publishers see embedded indexing’s main benefit as accelerating the production process. The indexing profession needs to encourage publishers to consider the other benefits as well.

Despite the benefits of embedded indexing, the publishing industry has been somewhat slow in adopting the method. This is not due to technology obstacles, but rather due to the need to adopt new publishing workflows when implementing embedded indexing.

Getting Started at Embedded Indexing – Information for Indexers

Resources on Embedded indexing