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Markup UK 2023 Proceedings
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XProc as a command-line application engine
Introduction
What is XProc?
The problem domain
Is XProc a suitable language?
Design pattern 1: Job tickets
The job ticket
Design pattern 2: Command line wrappers
Wrap-up and conclusions
Working with XML inside a web browser
Introduction
Project Goals
What new XML technologies are required?
Technical Challenges
The XML data model layer
The XML user interface layer
The XML program logic layer
The resulting architecture of the XML edge platform
The two projects
Future development for the two projects
Conclusion
Markup UK Proceedings as CSS
DocBook
DocBook Stylesheets
Comparing XSLT 1.0 and xslTNG Stylesheets
Localisation
Build system
Syntax highlighting
XSLT debugging
Cover pages
PDF bookmarks
Current status
Acknowledgements
Bibliography
Enhancing Markup Quality Assurance with Automated Schema Visualization
Introduction
Background and Related Work
Introducing the XSD Visualizer Plugin
Key Features for Assessing Schema Quality
Visualizing Inheritance Structure
Providing Effective Element and Type Structure
Jump-to-Code for Editing
Future Development
Enhancing the Schema Quality Workflow with Work-in-Progress Features
Tree View for Exploring the Actual Structure
Composite View for Understanding Complex Composition Structures
Implementation Details of the XSD Visualizer Plugin
Feedback and Future Development
Support for Additional Schema Formats
Potential Name Change to "SchemaViz"
Port to Visual Studio Code
HTML Export with SVG Graphics
Conclusion
Improving quality-critical XML workflows with XProc 3.0 pipelines
Introduction and background
About Thieme Compliance GmbH and patient education leaflets
About <xml-project /> and XProc
Introduction to existing batches
Batch “fragengruppe_2_evidence”
Batch “fragengruppe_2_FHIR-Questionnaire”
Pain points of the existing batches
Lacking of flexibility for inserting additional XSLT steps (in between)
No easy way to debug the intermediate results of each XSLT step
Too many tools means too many dependencies
New requirements for next version
Future-proof approach and improved maintainability by adding a separate orchestration layer
Increased quality through validation of XML sources using T0 XSD as well as validation of XML results using specific versions of T0 DTD
Increased quality by additional validation of XML results using Schematron
Summarised, formatted and easily comprehensible log files
Performance improvement by omitting unnecessary images from the Zip archive
Limiting processing to specific sources from the source folder
New system based on XProc 3.0
Takeaways
Smooth transition to XProc 3.0
MorganaXProc-IIIse worked well and could even be improved over the course of the project
Serialisation is now done by MorganaXProc and no longer by Saxon
Performance problems with FHIR XML schema
XProc pipeline optimisation by loading stylesheets only once at the beginning
Feature request for XProc: please add <p:validate-with-dtd>
Bibliography
Bridging the Gaps Between XML and TEX
Acknowledgements
Introduction
The Gaps Between XML and LaTeX
Methods to Convert XML to LaTeX
xmltex
PassiveTeX
Pandoc
XSLT
An Alternative Approach
Math Transform MathML to TeX
Transform XML to TeX
Issues
Conclusion
Building a cloud-based visual operating system entirely based on XML
Introduction
Finding a cure to the chaotic software landscape
What is CloudTop really?
Changing the perception of a computer
Verifying our assumptions
Looking through a few of the sample applications built
XMLPad - Data Manipulation and Transactions
Kanban - Hierarchical Data Model
Contacts - Key/values, Meta-data, and Datatypes
CloudTop - Combining Applications into a Desktop
Using TDD to produce High Quality XSLT
TDD : where does it comes from ?
The TDD loop and the refactoring phase
Writing a MarkDown to HTML converter with XSLT
Feature definition
Tooling
Methods
Implementation
Level 1 titles
Next titles and list items
Pro and Cons of using TDD for XSLT development
Bugs
Baby steps
Refactoring
Code Coverage
Data Coverage
Conclusion
Bibliography
Word processing is so last century
Executive Summary
What's computer-assisted sense making?
Onto-what?
Working with multiple languages, perspectives, and ontologies
How prodoc helped make sense of big words
Lessons learned
The path to prodoc
Bots hate word processing's ornery visually-oriented ontology
Semantic markup to the rescue
Separating structure and style
Integrating lifecycle perspectives
From semantic markup to semantic authoring
Individual impacts
Organizational impacts
Document-level controls to capture and communicate meaning
Author-driven structural changes
Author-driven visual changes
prodoc in practice
@class — Authored class styles
<awkbuddy/> — An interactive development environment block
<bbody/>, <branches/>, <branch/> — Hierarchical tables
<colortest/> — Automating accessible color negotiation pipelines
<h/> — Depth-based headings because big headings are ugly
<kfam/> — An element and generalized design language to make sense of knowledge flows from multiple perspectives
kfam conceptual language
kfam markup language
kfam visual language
kfam modeling
<music/> — Rationalizing chord/ lyric pairings
<vcanvas/> — Visualizing and comparing sets of value optimizations
WordNet and SUMO integrations — Associating markup with dictionaries & formal logic
Approach
Findings & next steps
Bottom-up negotiations to define shared meanings
h1.dtd — Build your own prodoc
h1.dtd summary
Leveraging the Power of OpenAI and Schematron for Content Verification and Correction
Introduction
Artificial Intelligence
Generative Pre-trained Transformer(GPT)
Schematron and AI
Schematron Quick Fix and AI
Implementation of AI in Schematron
Examples of AI-driven Schematron and SQF Solutions
Check text consistency
Check text voice
Answer to question
Check the number of words
Check if block of text should be a list
User-Entry - Check technical terms
Generate Fix Automatically
Develop Schematron using AI
Conclusion
XQS: A Native XQuery Schematron Implementation
Background
Rationale
Design goals
Conformance over performance
Dynamic evaluation
Portability
Caveats
Expansion and inclusion
"Native"?
Mandated XQuery QLB
Approach
Context is everything
Document level
Node level
Assertion level
Implementation
Dynamically evaluated schema
Evaluating patterns
The documents attribute
Rule processing
Advisory notes
Compiled schema
Other features
User-defined functions
Evaluating schema components
Maps, arrays and anonymous functions as variables
Unit testing
Evaluation
Status of the work
The conformance suite
Future work
Bibliography
Quality in Formatted Documents
Markup Quality
XSL-FO
CSS
Formatted Quality
Regression testing
Automated analysis
PDF/UA checking and remediation
A Dependency Management Approach for Document and Data Transformation Projects
Introduction
Introducing Apache Ivy
Starting with Arousa
A bold experiment. How much time/effort does it take?
Introducing the Arousa project structure
Ivy abstraction. Introducing artifact types
A Key difference with Maven
Configuration chains
The Ivy Cycle.
Ivy flexibility (resolvers)
Working with “Others”, the Dual resolvers
A step further
An advanced example
Conclusions
Bibliography
Tool-Based Transformations
Introduction
Project steps and phases
Exploring Data
Off-the-shelf tools and ad-hoc tools
Analyzing Existing Code
Doing The Actual Work
Conclusion
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