Webinars
DCL Learning Series
Upcoming Webinars
The DCL Learning Series covers topics that relate to content and data conversion with an instructional twist. DCL speaks with industry experts and brings meaningful presentations and conversation direct to your screen. Topics include research integrity, DITA, S1000D, Section 508 and accessibility, XML standards, PubMed, artificial intelligence, and much more.
Our webinar calendar is constantly updated. Click the link to receive alerts for upcoming webinars.
KEYWORDS:
artificial intelligence, fault isolation, S1000D, XML, legacy content, content conversion, automated conversion, maintenance documents, aerospace and defense, natural language processing, machine learning, technical publications, Data Conversion Laboratory
SPEAKERS:
Naveh Greenberg, Director, Defense Development,
Data Conversion Laboratory
Chuck Davis, S1000D and IETM Subject Matter Expert,
Data Conversion Laboratory
Balancing AI, Automation, and Manual Steps to Convert Fault Isolation From any Legacy Format
Wed, Dec 16, 2026 12:00 PM - 12:30 PM EDT
Balancing between artificial intelligence (AI), automation, and manual processes is critical when converting Fault Isolation (FI) content from legacy formats into S1000D XML. Legacy maintenance documents—often stored as unstructured PDFs, Word files, or proprietary databases—vary widely in structure and quality. AI technologies such as natural language processing (NLP) and machine learning can accelerate the conversion process. However, fully automated conversion is not always sufficient due to the complexity and safety-critical nature of technical publications, especially in aerospace and defense contexts.
Automation plays a key role in handling repetitive, rules-based transformations. For example, scripts and transformation engines can standardize terminology, enforce S1000D schema compliance, and restructure content into XML tags. Automated validation tools can also check business rules, metadata completeness, and schema correctness. This layer ensures consistency, scalability, and efficiency across large volumes of content.
However, automation depends heavily on well-defined mapping rules and high-quality source data; inconsistencies or ambiguities in legacy content can propagate errors if not carefully controlled. Manual intervention remains a key checkpoint in the conversion process. SMEs verify that the fault isolation logic is preserved correctly, especially where diagnostic branching or conditional steps are involved. They also resolve ambiguities, refine terminology, and ensure that the resulting S1000D modules are usable in real maintenance scenarios.
Ultimately, the most effective approach is a balanced one. You will leave this presentation understanding how this can be effectively accomplished with speed, accuracy, and confidence.