More Related Content Similar to Taxonomy 101: Classifying DITA Tasks (20) Taxonomy 101: Classifying DITA Tasks2. Poll: Please complete while folks arrive
How are you delivering DITA Tasks or other
procedural / how-to content?
• Portal with advanced / faceted search
• Static web pages or web help
• Print / PDF
• Windows Help
• Other
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3. Why talk about task oriented content?
Task-oriented content is
valuable:
• It is versatile and can be
reused in more
deliverables than
conceptual content
– Product user guides
– Context-sensitive help
– Knowledge base
– Support
– Training
• It’s what most users are
searching for in a
A DITA Task published to MindTouch
knowledge base or help
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4. Benefits of using DTA for authoring tasks
• Task authored in DITA are
– Concise
– Consistent
– Modular
– Semantic
• DITA Tasks make good
templates for content
contributed by SMEs (like
product engineers)
• For software UA in
particular, task-oriented
content is perfect for QA. The
task becomes the Test Case.
The XML Source for a DITA Task
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5. Anatomy of a DITA Task
• Title
• Short description
• Context
• Prerequisite
• Step section
• Step
• Command
• Sub Step
• Step Info
• Step Result
• Step Example
• Choice and Choice Table
• Example
• Post-requisite
• Result A DITA Task in easyDITA
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6. DITA Tasks are semantic
• DITA tasks are inherently semantic
– Not simple ordered lists
– Not simple paragraphs
• This is useful for
– Dynamic rendition, e.g.
• Expand / collapse steps
• Interactive UI controls
– Semantic Search in the context of the structure, e.g.
• find STEPS that contain MENU CASCADES
• Find STEP INFORMATION that contains IMAGES tagged with [text]
• Find PREREQUISITES that contain [text]
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7. Making tasks more findable with metadata
• Q: How can we make content
even more findable
– For authors and content
managers?
– For end users in a dynamic
delivery system?
• A: Tag tasks with semantic
metadata
– Semantic = “meaning”
– Metadata can be set with terms
from controlled vocabularies
defined and managed in a
taxonomy
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8. What is Metadata?
• Literally “Data about the data”
• Also known as “tags”
– Not to be confused with the content itself (e.g.
XML structure)
– Can be embedded in a file (e.g. the DITA Prolog
or attributes; JPEG image data) or associated in
a CMS
• Two main flavors:
– Administrative metadata
• e.g. Content Type, Author, Date
Modified, Version, Title, etc.,
• Usually system-generated
• What the content is
– Descriptive metadata
• Subject classification, keywords, etc.
• Usually manually authored
• What the content is about
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9. Key Concept: Taxonomy
taxonomy n. A categorization
scheme for concepts, often
hierarchical
• Most often, taxonomies show “is a”
relationships, e.g. A mammal is a
vertebrate, A rodent is a mammal, etc.
• Navigation up and down the tree yields
broader than (BT) and narrower than
(NT) classification
– Can be used to adjust search scope
• Can also show related terms (RT)
– Can be used to suggest related searches / “see
also”
• Can manage synonyms (UF – Use For)
– Can be used to find content when search
terms are not the preferred terms
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10. Using Taxonomy for controlled vocabularies
• A taxonomy is the “source of truth” for what terms to use for
various concepts – so terms are consistent.
• Taxonomy terms can be used as controlled vocabularies (“pick-
lists”) for metadata, so authors simply select preferred terms
– Avoids typos, duplicates, word form variations, use of non-preferred terms
• Some content management systems enable controlled
vocabularies from taxonomies to be used for setting attribute
values in DITA (e.g. selectatts like Audience, Product, Platform etc.).
• Relationships between terms in a Taxonomy can improve search
– CMS search and site search indexing tools can use equivalent and related
terms to find content that does not contain the search term
– Relationships between terms can be expressed as RDF in HTML content for
improving web search indexing
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11. Simple framework for tagging tasks
• In any industry, we’re all trying to help people do something to
something in a context:
– Who is doing what to what (+ other important context or condition)
• Examples
Junior Service Technician doing preventive maintenance on Acme Jetpack
XR7 that uses nitrous oxide injection technology
Casual User clearing paper jam on MFD100 Copier with envelope tray option
Case Worker performing an intake interview for a recently unemployed
person in New York State
Intermediate User publishing a DITA Map using DITA OT to PDF format
Financial analyst calculating a WACC for a publicly traded company located in
a country using GAPP accounting
Registered Nurse administering medication to patient in the ICU and drug is a
controlled substance
Contract Service Technician doing diagnosis on P1000 Printer showing missing
sections of the printed image
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12. What metadata do you need?
Information about the
Performer, Activity, Object, and Context will help
narrow search results for a user or author (see our
blog post on Metadata 101: A Search First Approach)
• Performer metadata:
– Types of users (roles, experience, education
level, etc.)
– Types of employees
(title, training, certifications, clearance, departmen
t, skill level etc.)
– Types of customers
• Activity metadata:
– Broad Task Types (e.g. for service:
maintenance, diagnosis, repair, calibration, startup,
etc.)
– High Level Task names from a performance analysis
/ instructional design
– Competencies from a model
–
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13. What metadata do you need?
Information about the
Performer, Activity, Object, and Context will help
narrow search results for a user or author (see our
blog post on Metadata 101: A Search First Approach)
• Object (i.e. “To what / to whom”) metadata:
– Things: Product, product components, product
subsystems
– People: Types of customers or clients
• Context metadata:
– Market / locale
– Product options
– Technologies
– Special situations
– Tools required
– Security classification
– Symptoms / Fault codes
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14. Do we have to create these terms from scratch?
No! You are surrounded by free sources for term lists, many are
governed and authoritative. Don’t reinvent – borrow!
Here are some common sources of terms:
• Corporate ECM or Web taxonomy (from IT or marketing)
• Industry-specific taxonomies (e.g. MeSH for life sciences, DSM for mental health)
• Government taxonomies (e.g. UK IPSV - Integrated Public Sector Vocabulary)
• Generic public domain taxonomies (e.g. People, Places, and Cultures; AP News)
• Other corporate sources:
– Training group (competency models, task analyses)
– HR (Job codes and Job Titles)
– Support / field service systems (Parts, fault classifications, failure modes, tools used)
– CRM data (Customer names, Customer categories, SKUs, Products & Services)
– Product data (Product BOMs, platforms, parts, subsystems, options)
– Organization Charts (Divisions, departments, locations, budget centers)
– Business Process Analysis (process names and steps, inputs and outputs)
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15. Taxonomy Tools
• You can build and manage a simple taxonomy in Microsoft Excel
• Even if authors manually tag metadata, the Excel taxonomy can be a useful
guide and source of terms to copy/paste
• Each row is a term and each column is a level in the hierarchy
• Put other data required for related and equivalent terms in columns to right of
preferred term hierarchy
• Add a column for scope notes
• Use Grouping to help expand / collapse sections of a long taxonomy
• If you have a CMS or other tool that consumes taxonomy, you can export a CSV
file from Excel and import it to the CMS (see Mary Garcia’s excellent blog posts at
TaxoDiary.com to learn how)
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16. Taxonomy Tools
• Consider using a Taxonomy Management System if:
– You have a large taxonomy (over 500 terms)
– The taxonomy changes often
– You have a complex governance process for approving new terms
– The taxonomy needs to be consumed by more than one system
– You are using term relationships to improve search indexing
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17. Guidelines for taxonomy quality
• The hierarchy should reflect any of three relationships:
– Generic (e.g. VehicleCar)
– Instance (e.g. Mountain regionsRockies)
– Whole-Part (e.g. HouseRoof)
• Terms should be nouns or noun phrases.
• Activities should be nouns or gerunds.
• Avoid adjectives and prepositions unless integral to the term.
• When in doubt singular vs. plural, choose plural; these are
categories. Singular is OK for instances at the narrow end.
• Named entities should be proper nouns.
• Avoid punctuation and ampersands. Eliminate hyphens except
where the term is confusing or unclear without them.
• Make the most commonly used term the preferred term, even if it
is an acronym (e.g. NASA). Make other forms Equivalent Terms.
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18. Poll:
Are you currently using controlled
vocabularies for any of the following?
• CMS Metadata
• DITA Attributes
• Prolog Metadata and Keywords
• Other
• Not using controlled vocabularies
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19. Resources
• LinkedIn Taxonomy Community of Practice
• ANSI/NISO Z39.19-2005 - Guidelines on
Construction, Format, and Management of Monolingual
Controlled Vocabularies
• IBM Presentation: Writing Effective DITA Task Topics
– http://svdig.ditamap.com/DITATaskTopics_090310SR.ppt
• TaxoDiary blog posts by Mary Garcia:
Maintaining a Thesaurus in an Excel Workbook (two parts)
– http://taxodiary.com/2012/04/maintaining-a-thesaurus-in-an-excel-
workbook/
– http://taxodiary.com/2012/05/maintaining-a-thesaurus-in-an-excel-
workbook-part-2/
• easyDITA blog posts and Twitter
– easyDITA.com/blog and @easydita
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20. Thank you!
• Questions?
• Recorded webcast will be available soon through our website –
you will get an email with the link
• Anyone can register after the event to view the recording
• Slides will be available on SlideShare
– www.slideshare.net/easydita
• Next webcast July 25, featuring Amber Swope of DITA Strategies
discussing Using Taxonomy for DITA Content. Please join us!
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