1. Alexander (‘Sasha’) Schwarzman, AGU Balisage 2011: The Markup Conference, Montréal, Canada Page 1 of 3
(sschwarzman@agu.org) August 2–5, 2011
Using Schematron for Appropriate Layer
Validation: a Case Study
Alexander (‘Sasha’) Schwarzman, AGU (sschwarzman@agu.org)
Balisage 2011: The Markup Conference, Montréal, Canada
August 2 – 5, 2011
Appropriate layer validation—advantages
 Even the most “Prussian” DTD cannot enforce all business rules, data types, and house style
 Rules-based checking needed anyway
 May use a “Californian” DTD, such as JATS: de facto industry standard adopted by publishers,
conversion and composition vendors, archives, etc.
 Can use tools developed for JATS: Preview XSLT stylesheets, EPUB conversion processes, etc.
Why Schematron?
 Multiple genres (document types)
 Journal article
 Book chapter
 Book
 Newspaper article
 Different lifecycle phases
 Papers in press (journal article)
 Initial validation (journal article, book chapter)
 Final validation (all genres)
Journal article

2. Alexander (‘Sasha’) Schwarzman, AGU Balisage 2011: The Markup Conference, Montréal, Canada Page 2 of 3
(sschwarzman@agu.org) August 2–5, 2011
Book chaper and book
Newspaper article

3. Alexander (‘Sasha’) Schwarzman, AGU Balisage 2011: The Markup Conference, Montréal, Canada Page 3 of 3
(sschwarzman@agu.org) August 2–5, 2011
AGU Schematrons
FBA IJA FJA SWN FBK EOM EOS PIP IBA
AGUcontribs.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
bibr-adhoc.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
bibr-ids.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
bibr-italics.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
bibr-structures.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
book-bookarticle.sch ✓
book-meta.sch ✓
bookarticle-meta-final.sch ✓ ✓
bookarticle-meta.sch ✓ ✓ ✓
common-back.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
common-final.sch ✓ ✓ ✓ ✓ ✓ ✓
common-meta.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
common.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
dates.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓
eos-only.sch ✓ ✓
filetypes.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
global.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
index-codes.sch ✓ ✓ ✓
index-terms.sch ✓ ✓ ✓ ✓ ✓ ✓
journalarticle-meta-final.sch ✓ ✓ ✓ ✓
journalarticle-meta.sch ✓ ✓ ✓ ✓ ✓ ✓
journalarticle-tech.sch ✓ ✓
mddb-ws.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
names.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
print-final.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
ref-misc.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
setup.sch ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
 9 top-level Schematrons, 27 modules
 350+ requirements checked
 Perform Web Services-based verifications against relational metadata database
 Check data quality, markup integrity, business rules, data types, and house style
 Provide control over production processes
 Work best in oXygen (context-sensitive), can be compiled and integrated into pipeline scripts
Paradigm shift: validation focus moves from XML parser to Schematron engine
☛ Content may be valid to the DTD but make no sense
☛ Semantic integrity now depends on Schematron
☛ Should each Schematron release be preserved and the version info added to metadata?
☛ Constraints on business partners: they must be Schematron-capable and have tools
☛ Schematron does not “fix” problems—people do! Processes & procedures must be defined
How to build a good
 Elicit, document, convey, and clarify the Requirements
Schematron
 Ensure Schematron fits into your workflow
 Modularize Schematron
 Ensure that individual Schematron rules aren’t in conflict
 Optimize Schematron performance
 Employ XSLT 2.0
 Test, test, test
 Cultivate Schematron & XSLT 2.0 expertise in-house