Content Quality Assurance

Healthy Content Begins With Quality Assurance

Customized Process For Your Project: Content Analysis I Setting Quality Standards I Automated QA

DCL's Content Quality Assurance (QA) is to provide independent reviews of converted results or to provide oversight for a do-it-yourself (in-house) or outsourced project. QA can be performed pre-conversion to catch errors early in the process or post-conversion to ensure no errors appear in the in the final product. DCL performs independent QA services for organizations such as ASTM, IEEE, NIH and more.

DCL Quality Assurance Platform

The DCL Quality Assurance Platform runs content against both its proprietary Harmonizer ™ module and then a customized and configured quality check process. These automated checks ensure conversion quality and verify that specification and best practices have been followed. DCL’s expertise in analyzing your document, providing compliance audits and remediating assures you a smooth process that meets all your schedules.


Download 'Case Study – Automated Auditing of S1000D Aircraft Manuals'

Case Study: For a deeper understanding, read our case study on our work with the Air Force where DCL developed customized QA software to optimize conversion results for their air craft manuals. The software was subject to rigorous testing and refining, requiring regular meetings with the manufacturer and the Air Force to update progress and discuss tweaks to maximize its efficacy.

Click here or the image on right for a Free download of this case study.

Article: Automated Auditing of S1000D Aircraft Manuals as featured in Aerospace Manufacturing & Design.

DCL handles all formats

Images, PDF, HTML, HTML5, SGML, XML (all schemas), MS-Word, and any others – all kinds of documents and web content in any language. Typical project include:

  • Working with you to conduct an initial content analysis with Harmonizer
  • Working with you to review and define a set of quality standards to run your content against
  • Working with you to easily automate the feeding of your content through a QA process and presenting the results through an easy to use UI

Analysis is the key first step in Quality Assurance

The first step in Content Quality Assurance is content analysis which helps to quickly identify areas for investigation.

  • Drive increased consistency
  • Reduce development timelines
  • Rapid reconfiguration
  • Find Typos or Applicability
  • Lower maintenance costs
  • Detect applicability and inconsistencies
  • Finding exact or similar text will help you when mapping to your Data Modules:

  • Structure/Content Tagging
  • Cross-References/Linking
  • Tables
  • Lists
  • Paragraphs, Heads, etc.
  • Front and Back Matter
  • Special Characters
  • Graphics
  • Index
  • Footnotes
  • Math
  • Table of Contents

The importance of having a plan and process for Content Quality Assurance

In today’s environment, especially with standards and regulations to meet, assuring your content quality is vitally important. Most content is an accumulation from various sources that builds up over time. Periodic review and analysis focuses efforts on identifying and improving ongoing content quality, consistency and accuracy.

Most organizations conduct this type of review and analysis around large conversion projects or large systems migrations. But these systems lack the ability to perform regular QA check-ups as content changes and grows over time, and in many cases, critical content spans systems and repositories. That’s why a plan and process for ongoing Content Quality Assurance is so critical.

Main challenges faced in assuring content quality

In most organizations, regular efforts to review content quality are extremely manual projects and the resources are simply not available. This has been the most significant barrier – the perception of a lack of easy automated tools to assist content experts and owners to make this a cost effective part of their ongoing operation. Content grows over time and quality issues arise from many sources, including:

  • Transferred text
  • Tables
  • Math & Special Characters
  • Incorrect hierarchy
  • Irrelevant, missed or incorrect Cross-References
  • Tagging structure completeness – especially in figures, images and diagrams
  • Out of date/incorrect metadata
  • Redundant content
  • Typos in data
  • Content tagging validity (proper alert tagging, placement)

Contact DCL today to get started on your path to Ongoing Content Quality Assurance.