If you've ever been faced with the challenges related to converting your data to XML, this webinar is for you! In addition to the basic challenges of converting data to XML, the conversion to S1000D has the complexity of Data Module Requirements List (DMRL), Applicability and other content driven tagging structures. Having a solid plan in place and identifying issues prior to conversion is imperative to the overall success of the project.

1. Welcome to an Information Session on
Managing the Complexities of Conversion to S1000D
Host: Tammy Halter, CEO, Absolute Data Group (ADG)
Presenter: Naveh Greenberg, Senior Project Manager,
Data Conversion Laboratory, Inc. (DCL)
Wednesday, 9 April 2014
Thursday, 10 April, 2014
Please ensure you have speakers on your computer or a headset
in order to hear the presentation. No telephone dial-in is
required.

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4. ADG’s R4i S1000D Product Suite
• R4i CSDB – Create, manage and publish critical content to IETP/IETM,
HTML and other Electronic Delivery
• R4i Viewer – Royalty-free online and offline IETM Viewer for an
advanced Interactive Electronic Technical Manual
• R4i Workbench – Easy to use, web-based S1000D Authoring tool for
faster authoring
• R4i Binder – Powerful ‘drag & drop’ tool for creating manuals,
handbooks and large technical books from S1000D

5. Naveh Greenberg
Naveh Greenberg is a Senior Project Manager for Data Conversion Laboratory,
Inc, and a PMI-Certified Project Management Professional (PMP) with
expertise in large-scale complex conversions utilizing numerous
DTD/Standards. He specializes in conversions for DCL’s Defense and Tech
Doc business units, and has been instrumental in developing DCL's DITA,
2361/40051, S1000D, and 38784 conversion software suites, as well as
working with clients to develop detailed project business rules.
Naveh is a member of the United States S1000D Management &
Implementation Group (USSMG) Land Working Group, and participates in
other discussion subgroups. He has been with DCL for over 10 years, and
holds a BE in Mechanical Engineering from Stony Brook University.

6. Managing the Complexities of
Conversion to S1000D

7. Experience the DCL Difference
DCL blends years of conversion experience with cutting-edge technology and
the infrastructure to make the process easy and efficient.
• World-Class Services
• Leading-Edge Technology
• Unparalleled Infrastructure
• US-Based Management
• Complex-Content Expertise
• 24/7 Online Project Tracking
• Automated Quality Control
• Global Capabilities

8. Valuable Content Transformed
• Document Digitization
• XML and HTML Conversion
• eBook Production
• Hosted Solutions
• Big Data Automation
• Conversion Management
• Editorial Services
• Harmonizer

9. We Serve a Very Broad Client Base . . .

10. . . . Spanning All Industries
• Aerospace
• Associations
• Defense
• Distribution
• Education
• Financial
• Government
• Libraries
• Life Sciences
• Manufacturing
• Medical
• Museums
• Periodicals
• Professional
• Publishing
• Reference
• Research
• Societies
• Software
• STM
• Technology
• Telecommunications
• Universities
• Utilities

11. Planning for a conversion to S1000D
• Ask the important initial questions
• Who are the stakeholders. Who is the final client/user?
• What is the estimated volume and deadline?
• What version of S1000D?
• Do we know what CMS or rendering tools will be used?
• Source format. Not all source data are created equal.
• Budget?
• Ask around or join discussion groups.
• Prepare for the next step
• Get your hands on the source data, business rules, and schemas.
• Begin looking for the right people. You don’t need to be a S1000D savvy
but you do at a minimum understand the concept.
“If I had eight hours to chop down a tree, I'd spend six sharpening my ax.”

12. What is your source data?
• Paper or scanned PDF
• PDF Normal
• Electronic – WORD, Indesign, FM….
• Electronic – SGML or XML
• All of the above

13. Planning for a conversion to S1000D
• Ask the important initial questions
• Who are the stakeholders. Who is the final client/user?
• What is the estimated volume and deadline?
• What version of S1000D?
• Do we know what CMS or rendering tools will be used?
• Source format. Not all source data are created equal.
• Budget?
• Ask around or join discussion groups.
• Prepare for the next step
• Get your hands on the source data, business rules, and schemas.
• Begin looking for the right people. You don’t need to be a S1000D savvy
but you do at a minimum understand the concept.
“If I had eight hours to chop down a tree, I'd spend six sharpening my ax.”

14. What is your S1000D level?
• Savvy
• Knowledgeable
• Getting started
• Forced into it
• First time hearing about it

15. The importance of analysis as the first step in conversion
• It will help you to:
• Properly scope the project.
• Understand source data structure and inconsistencies.
• Have a general idea of what Data Modules will or will not be used.
• Estimate SME involvement.
• Figure out if re authoring is needed.
• Plan a head on what requires automated QC checks and estimate what
must be done manually.
• Minimize the risk of finding "surprised" in the middle of the conversion
process.

16. The importance of analysis as the first step in conversion (2)
• Fixing issues later can be very costly.
• For example a 5000 page project:
• 5 minutes per page to fix
• 25,000 minutes => 417 hours
• At 7 hours per day (no breaks) => 59.6 days
• But worse ...
• Tagging is inconsistent
• IETM/CMS may not properly function

17. The importance of analysis as the first step in conversion (3)
• Example: Automated Links
• See figure 15.5
• Refer to fig. 15.5
• See figures 15-5, 15-6 and 15-9 thru 15-13
• Refer to paragraph 5.6
• However…
• Refer to the figure below
• As illustrated on previous page
• … drawing 15.5 years at hard labor.
• See figure 15.1 in volume II of …
• Replace part per 6.3.2, steps 5 thru 8.

18. Idiosyncrasies to identify early in the process
• Flagging headings – will be used in the DMRL
• Missing required text (for example preliminary requirements)
• “extra” text (such as “do the following steps”) that doesn’t fit S1000D
structure.
• Content Tables downgrade to CALS Tables
• Auto-generated Text – If not cautious can cause duplicated text but if
properly used should help you in automation.
• How to handle graphics
• Conflicts with Business Rules
• Identifying proper Data Module Code/Information Code.
• Introductory paragraphs or requirements that apply to more than one Data
Module.

19. Idiosyncrasies to identify early in the process (1)
Re-author may be needed however in most cases you will need to
find patterns, develop special rules and restructuring.
If it was consistent, the process would be simplified
Section I. Introduction
1-1 Scope
1-2. Theory of Operation
1-2.1 Engine
Chapter 1
Section I. Introduction
Section II. Procedures
1-1 General Information
1-2. Repair Engine
1-3 Clean Engine
Chapter 2
<description>
<description>
<description>
<description>
<description>
<description>
<procedure>
<procedure>

20. Idiosyncrasies to identify early in the process (2)
IPD
Wiring
Descriptive
Crew
Fault
Appendix B
Procedural
Para 1-1Early S1000D
Publication
Para 1-2
Para 1-3
Para 1-1
Para 3-1
Para 2-1
PDF Book
Para 1-2
38784 Book
Para 2-1
Para 2-2
Appendix A
Para 3-2
Appendix A
Appendix B
S1000D Common Source Database
Publication 1
Publication2
Subtask
Task
Subtask
ATA Book
Pageblock
Pageblock
Pageblock
Pageblock
Pageblock
Task
Maintenance
Process
Descriptive DM
Procedural DM
IPD DM
Wiring DM
Crew DM
Process DM
Maintenance DM
Fault DM
IPD
Wiring
Descriptive
Crew
Fault
Procedural
Maintenance
Process
Process
Wiring
Procedural
Descriptive
Fault
Crew
Process
Publication3

21. Idiosyncrasies to identify early in the process (3)
• Finding exact or similar text will help you when mapping to Data Modules
• It will also help to detect applicability and inconsistencies

22. Idiosyncrasies to identify early in the process
• Flagging headings – will be used in the DMRL
• Missing required text (for example preliminary requirements)
• “extra” text (such as “do the following steps”) that doesn’t fit S1000D
structure.
• Content Tables downgrade to CALS Tables
• Auto-generated Text – If not cautious can cause duplicated text but if
properly used should help you in automation.
• How to handle graphics
• Conflicts with Business Rules
• Identifying proper Data Module Code/Information Code.
• Introductory paragraphs or requirements that apply to more than one Data
Module.

23. Idiosyncrasies to identify early in the process (4)
Printed Reference:
3-3. Operation of Main Switchboard. Do the following steps:
1. With emergency power ON, set all circuit breakers to OFF.
2. Refer to paragraph 3-44.
Example 1 – This will parse:
<para>3-3.<emphasis type="uline">Operation of Main Switchboard.</emphasis> Do the
following steps: </para>
<para>1. With emergency power ON, set all circuit breakers to OFF. </para>
<para>2. Refer to paragraph 3-44.</para>
Example 2 – This will also parse and tagged correctly:
<mainProcedure id="par3-3">
<dmTitle> … Operation of Main Switchboard. … </dmTitle>
<mainProcedure><proceduralStep><para>With emergency power ON, set all circuit breakers to
OFF.</para></proceduralStep>
<proceduralStep><para>Refer to <dmRef><dmRefIdent><dmCode … /> </dmRefIdent>
</dmRef>
</para></proceduralStep> ….

24. Idiosyncrasies to identify early in the process (5)

25. Idiosyncrasies to identify early in the process
• Flagging headings – will be used in the DMRL
• Missing required text (for example preliminary requirements)
• “extra” text (such as “do the following steps”) that doesn’t fit S1000D
structure.
• Content Tables downgrade to CALS Tables
• Auto-generated Text – If not cautious can cause duplicated text but if
properly used should help you in automation.
• How to handle graphics
• Conflicts with Business Rules
• Identifying proper Data Module Code/Information Code.
• Introductory paragraphs or requirements that apply to more than one Data
Module.

26. Idiosyncrasies to identify early in the process (6)

27. Idiosyncrasies to identify early in the process (7)

28. Idiosyncrasies to identify early in the process (8)
DUMMY VALUE
DUMMY VALUE
DUMMY
VALUE 1
DUMMY
VALUE 2

29. Idiosyncrasies to identify early in the process (9)
<pmcstable>
<title id="tbl2-2">Preventive Maintenance Checks and Services</title>
<pmcs-entry>
<itemno>1</itemno>
<interval>Before</interval> <interval>After</interval> <interval>Weekly</interval>
<manhours>0.04</manhours>
<checked>DUMMY VALUE</checked>
<pmcsproc>
<pmcsstep1>
<specpara><warning><para>Improper handling will cause death</para></warning>
<para>Inspect shelter exterior</para></specpara>
<pmcsstep2><para>Make sure area is clean</para></pmcsstep2>
</pmcsstep1>
</pmcsproc>
</pmcs-entry>
</pmcstable>

30. Idiosyncrasies to identify early in the process
• Flagging headings – will be used in the DMRL
• Missing required text (for example preliminary requirements)
• “extra” text (such as “do the following steps”) that doesn’t fit S1000D
structure.
• Content Tables downgrade to CALS Tables
• Auto-generated Text – If not cautious can cause duplicated text but if
properly used should help you in automation.
• How to handle graphics
• Conflicts with Business Rules
• Identifying proper Data Module Code/Information Code.
• Introductory paragraphs or requirements that apply to more than one Data
Module.

31. Idiosyncrasies to identify early in the process (10)
Printed Reference:
Introduction
The following procedures should be done.
Procedure
WARNING: Improper handling will cause death
1. With emergency power ON, set all circuit breakers to OFF.
Result: No electricity
2. Refer to paragraph 3-44.
END OF PROCEDURE
Tagging might be as follow:
<Intro><para>The following procedures should be done.</para> </Intro>
<Procedure><warning><para>Improper handling will cause death</para></warning>
<step><para>With emergency power ON, set all circuit breakers to OFF. </para>
<Result>No electricity</Result></step>
<step><para>2. Refer to paragraph 3-44.</para></step>
</Procedure>

32. Idiosyncrasies to identify early in the process
• Flagging headings – will be used in the DMRL
• Missing required text (for example preliminary requirements)
• “extra” text (such as “do the following steps”) that doesn’t fit S1000D
structure.
• Content Tables downgrade to CALS Tables
• Auto-generated Text – If not cautious can cause duplicated text but if
properly used should help you in automation.
• How to handle graphics
• Conflicts with Business Rules
• Identifying proper Data Module Code/Information Code.
• Introductory paragraphs or requirements that apply to more than one Data
Module.

33. Idiosyncrasies to identify early in the process (11)

34. Idiosyncrasies to identify early in the process
• Flagging headings – will be used in the DMRL
• Missing required text (for example preliminary requirements)
• “extra” text (such as “do the following steps”) that doesn’t fit S1000D
structure.
• Content Tables downgrade to CALS Tables
• Auto-generated Text – If not cautious can cause duplicated text but if
properly used should help you in automation.
• How to handle graphics
• Conflicts with Business Rules
• Identifying proper Data Module Code/Information Code.

35. Idiosyncrasies to identify early in the process (12)
Para No Original Title DMC Type Modelic
FOREWORD SAMPLESYSTEM-A-00-00-00-00A-018A-D Desc SAMPLESYSTEM
1 INTRODUCTION. -------
2 MANUAL ORGANIZATION. -------
CHAPTER 3
PREPARATION FOR USE AND
RESHIPMENT
NA
SECTION I PREPARATION FOR USE SAMPLESYSTEM-A-00-00-00-00A-006A-A Desc SAMPLESYSTEM
3.1 INTRODUCTION. -------
3.1.1
Nomenclature Setup and Initialization
Instructions.
SAMPLESYSTEM-A-00-00-00-00A-007A-A proc SAMPLESYSTEM
SECTION II PREPARATION FOR RESHIPMENT SAMPLESYSTEM-A-00-00-00-00A-530A-A Desc SAMPLESYSTEM
3.2 INTRODUCTION. -------
3.3
CONDITIONS AND METHODS OF
RESHIPMENT.
-------
CHAPTER 8 ILLUSTRATED PARTS BREAKDOWN SAMPLESYSTEM-A-00-00-00-00A-018B-D Desc SAMPLESYSTEM
SECTION I INTRODUCTION NA
8.1 INTRODUCTION. -------
8.2 MAINTENANCE PARTS LIST. -------
SECTION II MAINTENANCE PARTS LIST SAMPLESYSTEM-A-00-00-00-00A-075A-D IPB SAMPLESYSTEM
SECTION III NUMERICAL INDEX N/A
SECTION IV REFERENCE DESIGNATOR INDEX N/A
GLOSSARY SAMPLESYSTEM-A-00-00-00-00A-006A-D Desc SAMPLESYSTEM

36. Idiosyncrasies to identify early in the process (13)

37. Lessons learned
• Automate QC leads to more consistent and accurate results however not
always the most efficient way to go.
• Some visual QC is still required for:
• Table
• Images
• Missing text.
• Everyone must understand all the business rules uniformly.
• Always have a pilot or a limited production run before you convert all your
data.
• In legacy conversion you must be flexible.
• Think about sustainment.

38. Any Questions?

39. Q&A
Naveh Greenberg
Senior Project Manager, DCL
NGreenberg@dclab.com
Tammy Halter
CEO, ADG
thalter@absolutedata.com

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