SlideShare a Scribd company logo
How to board
a moving train
Managing DITA content models in
a live production environment
Bill Burns
• Content Architect
• XML/CCMS Consultant
What is specialization?
Healthwise
Regional Rail Line
• Heavy topic specialization
• Rapidly evolving model
• Complicated deployment process
• Complex manufacturing dependencies
Topic
specializations
run amok
• New semantics
• Very restrictive model
• 13 Healthwise-specific topic types
• Constraints on most block and inline elements
• Very restrictive model
Rapidly evolving content
model
• New elements needed
• Old specializations
unused
• New products required
new semantics
• Everything still has to map
to legacy transforms
Complicated
deployment process
• Multiple locations to be updated
• Six different systems or tools to be tested
• Three separate environments (Dev, Test,
Prod)
Complex manufacturing
dependencies
• 9 delivery channels
• 4 engineering teams
• Legacy product with proprietary schema
• Integrations with various EMR platforms
• Automated rebuild process for articles with
updated topics
What changed and
when?
• New content architect with DITA
experience
• Control over content model moved
from engineering to content
• Source-code repository added
• DTD shells refactored
• XSD generation put into place
What practices
helped or hurt
• Overloading attributes like outputclass (hurt)
• Specializing before assessing operational
impacts (hurt, kinda)
• More careful content analysis with end product
(helped)
• More direct engagement with engineering and
product management (helped)
How would we do
things differently
• Consider operational impacts
• Slow down on specializing
• Align all downstream channels from the
beginning
• Include translation and localization in the
consultation period
• Listen to our consultants!
What innovations did we
implement
• Structured content
pipeline
• Taxonomy integration
• Autoplaying of
deliverables
• JSON transforms and
APIs
• Cross-system search
functionality
• Pre-delivery previews
What is our plan for
the future?
• MOAR!
• Removal of legacy processing
• AI! Chatbots! Decision aids! Automation!
Why does it
matter to us?
• Our mission
• Our focus
• Our people
Q&A
Bill Burns
Content Architect
208.331.6917
bburns@healthwise.org
Contact

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Bill Burns - How to Board a Moving Train: Managing DITA Content Models in a Live Production Environment

  • 1.
  • 2. How to board a moving train Managing DITA content models in a live production environment
  • 3. Bill Burns • Content Architect • XML/CCMS Consultant
  • 5. Healthwise Regional Rail Line • Heavy topic specialization • Rapidly evolving model • Complicated deployment process • Complex manufacturing dependencies
  • 6. Topic specializations run amok • New semantics • Very restrictive model • 13 Healthwise-specific topic types • Constraints on most block and inline elements • Very restrictive model
  • 7. Rapidly evolving content model • New elements needed • Old specializations unused • New products required new semantics • Everything still has to map to legacy transforms
  • 8. Complicated deployment process • Multiple locations to be updated • Six different systems or tools to be tested • Three separate environments (Dev, Test, Prod)
  • 9. Complex manufacturing dependencies • 9 delivery channels • 4 engineering teams • Legacy product with proprietary schema • Integrations with various EMR platforms • Automated rebuild process for articles with updated topics
  • 10. What changed and when? • New content architect with DITA experience • Control over content model moved from engineering to content • Source-code repository added • DTD shells refactored • XSD generation put into place
  • 11. What practices helped or hurt • Overloading attributes like outputclass (hurt) • Specializing before assessing operational impacts (hurt, kinda) • More careful content analysis with end product (helped) • More direct engagement with engineering and product management (helped)
  • 12. How would we do things differently • Consider operational impacts • Slow down on specializing • Align all downstream channels from the beginning • Include translation and localization in the consultation period • Listen to our consultants!
  • 13. What innovations did we implement • Structured content pipeline • Taxonomy integration • Autoplaying of deliverables • JSON transforms and APIs • Cross-system search functionality • Pre-delivery previews
  • 14. What is our plan for the future? • MOAR! • Removal of legacy processing • AI! Chatbots! Decision aids! Automation!
  • 15. Why does it matter to us? • Our mission • Our focus • Our people
  • 16. Q&A