Field-Level Documentation Architecture to Reduce Duplication and Drift
Situation
A large DITA-based documentation set supported multiple related applications. The same data fields appeared on many screens and across products, often with different user interface labels. Field information was documented repeatedly inside task topics, with no shared source for field-level descriptions.
Problem
Because field information was embedded in many task topics, small differences accumulated over time. Field descriptions drifted, updates required touching many topics, and writers were unsure where field information should live. The documentation became increasingly difficult to maintain as the system evolved.
Architectural Approach
I analyzed how field information was being documented and identified data fields that appeared in multiple locations. I designed a structural approach where field-level information was documented once as shared content and referenced by screen and task topics, rather than rewritten in each context.
I clarified the boundary between:
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Field descriptions (what the field is and how it behaves)
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Task instructions (what the user does)
To support this structure at scale, I use an AI-assisted workflow to generate DITA field reference topics from screen captures, improving consistency and reducing manual effort.
Key Decisions
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Define field descriptions as standalone, reusable content
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Allow controlled contextual nuance without duplicating core field information
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Require task and screen topics to reference shared field descriptions
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Avoid embedding field definitions directly inside task steps
Results
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A single source of truth for field-level information
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Reduced duplication across task and screen topics
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Easier updates when fields changed
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Improved consistency across documentation
Why This Matters
Field-level architecture reduces long-term maintenance effort by preventing documentation drift at the data level. This approach scales well as systems grow and supports consistent documentation without constraining legitimate contextual differences.
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