SlideShare une entreprise Scribd logo
1  sur  24
Components of WordprocessingML
• Main Document
• Paragraphs & Rich Formatting
– Runs
– Run Content
• Tables
• Custom Markup
• Sections
• Styles
– Paragraph
– Character
– Numbering
– Table
– Document Defaults
• Fonts
• Numbering
• Headers/Footers
• Footnotes/Endnotes
• Glossary Document
• Annotations
– Comments
– Revisions
– Bookmarks
• Mail Merge
• Document Settings
– Web Settings
– Compatibility Settings
• Fields & Hyperlinks
• Odds & Ends (Textboxes, Subdocuments, Extensibility)
Ecma/TC45/2006/168
WordprocessingML – Mail Merge
Mail Merge
• Mail merge refers to a process by which a
WordprocessingML document is:
– Connected to external data sources
– Populated with external data
• The information about what data source top
connect to, and where to put that data is part
of WordprocessingML
– The actual merge is a runtime operation
Mail Merge Documents
• A mail merge document can exist in two
states:
– A source document, the document that contains
the data needed to connect to an external data
source for a mail merge
– A merged document, the document that contains
the data above *plus* the values from and a
reference to a single record from that data source
• One source document creates many merged
documents
Source Document Data
• The presence of a mailMerge element creates
a source document
• The data connection information is then
stored in the mailMerge element:
– Where the external data is located
– Type of external data
– The query to be run against that data
Source Document Data Example
Connection
String
Query
Link to Data
Source
Document
‘Type’
Source Document Content
• A source document contains the contents of a
standard WordprocessingML document with:
– Static content such as paragraphs and tables
– Mail merge fields that specify the location of the
external data within this static document content
Source Document Content Example
• Standard
WordprocessingML
document with:
– Two mail merge
fields for Courtesy
Title and Last Name
– Static content such
as paragraphs and
tables
Importing External Data
• Once we have a source document and the
ability to connect to data, we need to do
something with it
– i.e. perform the mail merge
• This is done via mail merge fields,
WordprocessingML fields that server as
markers for a particular column of external
data
Importing External Data (cont.)
• Mail merge fields can have two types of
references to column data:
– The column name from the data source
– A mapped name (a mapping to a predefined set
of merge field names with WordprocessingML)
• The latter is present to create one standard
set of field names regardless of data source
(e.g. to create standard address blocks)
Importing External Data Example
• Two mail merge
fields for Courtesy
Title and Last Name
• These are mapped
fields, so we need to
map these
predefined names to
columns in the data
source
Field Mappings
• The information linking a column to the
database column name and a mapped name
• A single field mapping contains:
– A column number
– The field mapping type
– The data source’s column name
– (optionally) A mapping to a predefined merge
field name
Field Mappings Example
• Looking at the first
field map:
– The fifth column
– Is a database
column
– Has a database name
of Content Model
– And a mapping to a
predefined name of
Job Title
Field Mappings Example (cont.)
• The resulting mapping allows the content of
that fifth column to be referenced by:
– A merge field specifying Content Model
– A merge field specifying Job Title
The Merged Document
• A merged document is the result of the mail
merge operation against a source document:
– The information to connect to the data source
– A cache of the contents of a single record
– A reference to that record
Merged Document Example
• Once a source document’s mail merge fields
have been mapped to external data, an
application may populate the fields with
external data
• Consider a source document from the
previous example
– Assume the external data source has one record:
Mr. Doe
Merged Document Example (cont.)
• A document is created containing:
– The static contents of the source document
– A single record of the external data
• In other words, a merged document is
generated as a result of the mail merge
Merged Document Example (cont.)
Appendix
• Predefined WordprocessingML merge field
names:
– Unique Identifier
– Courtesy Title
– First Name
– Middle Name
– Last Name
– Suffix
Appendix (cont.)
• Merge field names (cont.)
– Nickname
– Job Title
– Company
– Address 1
– Address 2
– City
– State
Appendix (cont.)
• Merge field names (cont.)
– Postal Code
– Country or Region
– Business Phone
– Business Fax
– Home Phone
– Home Fax
– E-mail Address
Appendix (cont.)
• Merge field names (cont.)
– Web Page
– Spouse Courtesy Title
– Spouse First Name
– Spouse Last Name
– Spouse Nickname
– Phonetic Guide for First Name
– Phonetic Guide for Last Name
Appendix (cont.)
• Merge field names (cont.)
– Address 3
– Department
Disclaimer
This presentation is for informational purposes only, and should
not be relied upon as a substitute or replacement for Microsoft
formal file format documentation, which is available at the
following website: https://msdn.microsoft.com/en-
us/library/cc313118(v=office.12).aspx. Any views or opinions
presented in this material are solely those of the author and do
not necessarily represent those of Microsoft. Microsoft
disclaims all liability for mistakes or inaccuracies in this
presentation.

Contenu connexe

Tendances

SessionFive_ImportingandExportingData
SessionFive_ImportingandExportingDataSessionFive_ImportingandExportingData
SessionFive_ImportingandExportingDataHellen Gakuruh
 
Indexing and Hashing
Indexing and HashingIndexing and Hashing
Indexing and Hashingsathish sak
 
Concept of computer files
Concept of computer filesConcept of computer files
Concept of computer filesSamuel Igbanogu
 
Indexing and hashing
Indexing and hashingIndexing and hashing
Indexing and hashingJeet Poria
 
File organization and indexing
File organization and indexingFile organization and indexing
File organization and indexingraveena sharma
 
Range Query on Big Data Based on Map Reduce
Range Query on Big Data Based on Map ReduceRange Query on Big Data Based on Map Reduce
Range Query on Big Data Based on Map ReduceIJMER
 
Intro databases (Table, Record, Field)
Intro databases (Table, Record, Field)Intro databases (Table, Record, Field)
Intro databases (Table, Record, Field)Maryam Fida
 
Data indexing presentation
Data indexing presentationData indexing presentation
Data indexing presentationgmbmanikandan
 
Database Management System
Database Management SystemDatabase Management System
Database Management SystemMuhd Dembo
 
Dbms quries
Dbms quriesDbms quries
Dbms quriesAns Ali
 
Starting ms access 2010
Starting ms access 2010Starting ms access 2010
Starting ms access 2010Bryan Corpuz
 
Database Fundamentals
Database FundamentalsDatabase Fundamentals
Database Fundamentalswmassie
 

Tendances (20)

SessionFive_ImportingandExportingData
SessionFive_ImportingandExportingDataSessionFive_ImportingandExportingData
SessionFive_ImportingandExportingData
 
Indexing and Hashing
Indexing and HashingIndexing and Hashing
Indexing and Hashing
 
Concept of computer files
Concept of computer filesConcept of computer files
Concept of computer files
 
Indexing and hashing
Indexing and hashingIndexing and hashing
Indexing and hashing
 
Ms access
Ms accessMs access
Ms access
 
File organization and indexing
File organization and indexingFile organization and indexing
File organization and indexing
 
indexing and hashing
indexing and hashingindexing and hashing
indexing and hashing
 
Isam
IsamIsam
Isam
 
Indexing and hashing
Indexing and hashingIndexing and hashing
Indexing and hashing
 
itft-File design
itft-File designitft-File design
itft-File design
 
Range Query on Big Data Based on Map Reduce
Range Query on Big Data Based on Map ReduceRange Query on Big Data Based on Map Reduce
Range Query on Big Data Based on Map Reduce
 
Intro databases (Table, Record, Field)
Intro databases (Table, Record, Field)Intro databases (Table, Record, Field)
Intro databases (Table, Record, Field)
 
Data indexing presentation
Data indexing presentationData indexing presentation
Data indexing presentation
 
Lec 1 indexing and hashing
Lec 1 indexing and hashing Lec 1 indexing and hashing
Lec 1 indexing and hashing
 
Database Management System
Database Management SystemDatabase Management System
Database Management System
 
Dbms quries
Dbms quriesDbms quries
Dbms quries
 
File organisation
File organisationFile organisation
File organisation
 
Database Management
Database ManagementDatabase Management
Database Management
 
Starting ms access 2010
Starting ms access 2010Starting ms access 2010
Starting ms access 2010
 
Database Fundamentals
Database FundamentalsDatabase Fundamentals
Database Fundamentals
 

En vedette

Mail merge 1_without_questions
Mail merge 1_without_questionsMail merge 1_without_questions
Mail merge 1_without_questionsSkript
 
The Power Of Mail Merge!
The Power Of Mail Merge!The Power Of Mail Merge!
The Power Of Mail Merge!Rina Banerjee
 
Proof reading, editing and revising by sohail ahmed
Proof reading, editing and revising by sohail ahmedProof reading, editing and revising by sohail ahmed
Proof reading, editing and revising by sohail ahmedSohail Ahmed Solangi
 
State of the Word 2011
State of the Word 2011State of the Word 2011
State of the Word 2011photomatt
 

En vedette (6)

Mail merge 1_without_questions
Mail merge 1_without_questionsMail merge 1_without_questions
Mail merge 1_without_questions
 
The Power Of Mail Merge!
The Power Of Mail Merge!The Power Of Mail Merge!
The Power Of Mail Merge!
 
Proof reading, editing and revising by sohail ahmed
Proof reading, editing and revising by sohail ahmedProof reading, editing and revising by sohail ahmed
Proof reading, editing and revising by sohail ahmed
 
Libre Office Writer Lesson 5: Mail Merge
Libre Office Writer Lesson 5: Mail MergeLibre Office Writer Lesson 5: Mail Merge
Libre Office Writer Lesson 5: Mail Merge
 
Mail merge
Mail mergeMail merge
Mail merge
 
State of the Word 2011
State of the Word 2011State of the Word 2011
State of the Word 2011
 

Similaire à WordprocessingML Mail Merge Components

Word 2007 unit h
Word 2007 unit hWord 2007 unit h
Word 2007 unit hsmgibbs
 
15 wordprocessing ml subject - fields and hyperlinks
15   wordprocessing ml subject - fields and hyperlinks15   wordprocessing ml subject - fields and hyperlinks
15 wordprocessing ml subject - fields and hyperlinksShawn Villaron
 
Wt-UNNIT-1 (1).ppt
Wt-UNNIT-1 (1).pptWt-UNNIT-1 (1).ppt
Wt-UNNIT-1 (1).pptGReshma10
 
Back to Basics 1: Thinking in documents
Back to Basics 1: Thinking in documentsBack to Basics 1: Thinking in documents
Back to Basics 1: Thinking in documentsMongoDB
 
Schema Design
Schema DesignSchema Design
Schema DesignMongoDB
 
16 wordprocessing ml subject - odds and ends
16   wordprocessing ml subject - odds and ends16   wordprocessing ml subject - odds and ends
16 wordprocessing ml subject - odds and endsShawn Villaron
 
4 wordprocessing ml subject - custom markup
4   wordprocessing ml subject - custom markup4   wordprocessing ml subject - custom markup
4 wordprocessing ml subject - custom markupShawn Villaron
 
14 wordprocessing ml subject - settings
14   wordprocessing ml subject - settings14   wordprocessing ml subject - settings
14 wordprocessing ml subject - settingsShawn Villaron
 
xMLDataModel.pdf
xMLDataModel.pdfxMLDataModel.pdf
xMLDataModel.pdfPrerak10
 
Systems Analyst and Design - Data Dictionary
Systems Analyst and Design -  Data DictionarySystems Analyst and Design -  Data Dictionary
Systems Analyst and Design - Data DictionaryKimberly Coquilla
 
3-Application Layer.pptx
3-Application Layer.pptx3-Application Layer.pptx
3-Application Layer.pptxSachinDUpadhye
 
Mail merge, cross referencing
Mail merge, cross referencingMail merge, cross referencing
Mail merge, cross referencingBanukaVidusanka
 
1 wordprocessing ml subject - main document
1   wordprocessing ml subject - main document1   wordprocessing ml subject - main document
1 wordprocessing ml subject - main documentShawn Villaron
 
2 wordprocessing ml subject - paragraphs and rich formatting
2   wordprocessing ml subject - paragraphs and rich formatting2   wordprocessing ml subject - paragraphs and rich formatting
2 wordprocessing ml subject - paragraphs and rich formattingShawn Villaron
 
SharePoint and Open XML
SharePoint and Open XMLSharePoint and Open XML
SharePoint and Open XMLBecky Bertram
 
Chapter 9 Data Design .pptxInformation Technology Project Management
Chapter 9 Data Design .pptxInformation Technology Project ManagementChapter 9 Data Design .pptxInformation Technology Project Management
Chapter 9 Data Design .pptxInformation Technology Project ManagementAxmedMaxamuudYoonis
 
michael hamilton legal database design presentation 3 new york
michael hamilton legal database design presentation 3 new yorkmichael hamilton legal database design presentation 3 new york
michael hamilton legal database design presentation 3 new yorkmichaelhamilton
 

Similaire à WordprocessingML Mail Merge Components (20)

Word 2007 unit h
Word 2007 unit hWord 2007 unit h
Word 2007 unit h
 
15 wordprocessing ml subject - fields and hyperlinks
15   wordprocessing ml subject - fields and hyperlinks15   wordprocessing ml subject - fields and hyperlinks
15 wordprocessing ml subject - fields and hyperlinks
 
Wt-UNNIT-1 (1).ppt
Wt-UNNIT-1 (1).pptWt-UNNIT-1 (1).ppt
Wt-UNNIT-1 (1).ppt
 
Xmll
XmllXmll
Xmll
 
Uses of MS Access in Business
Uses of MS Access in BusinessUses of MS Access in Business
Uses of MS Access in Business
 
Back to Basics 1: Thinking in documents
Back to Basics 1: Thinking in documentsBack to Basics 1: Thinking in documents
Back to Basics 1: Thinking in documents
 
Schema Design
Schema DesignSchema Design
Schema Design
 
16 wordprocessing ml subject - odds and ends
16   wordprocessing ml subject - odds and ends16   wordprocessing ml subject - odds and ends
16 wordprocessing ml subject - odds and ends
 
4 wordprocessing ml subject - custom markup
4   wordprocessing ml subject - custom markup4   wordprocessing ml subject - custom markup
4 wordprocessing ml subject - custom markup
 
14 wordprocessing ml subject - settings
14   wordprocessing ml subject - settings14   wordprocessing ml subject - settings
14 wordprocessing ml subject - settings
 
xMLDataModel.pdf
xMLDataModel.pdfxMLDataModel.pdf
xMLDataModel.pdf
 
Systems Analyst and Design - Data Dictionary
Systems Analyst and Design -  Data DictionarySystems Analyst and Design -  Data Dictionary
Systems Analyst and Design - Data Dictionary
 
3-Application Layer.pptx
3-Application Layer.pptx3-Application Layer.pptx
3-Application Layer.pptx
 
Mail merge, cross referencing
Mail merge, cross referencingMail merge, cross referencing
Mail merge, cross referencing
 
1 wordprocessing ml subject - main document
1   wordprocessing ml subject - main document1   wordprocessing ml subject - main document
1 wordprocessing ml subject - main document
 
2 wordprocessing ml subject - paragraphs and rich formatting
2   wordprocessing ml subject - paragraphs and rich formatting2   wordprocessing ml subject - paragraphs and rich formatting
2 wordprocessing ml subject - paragraphs and rich formatting
 
SharePoint and Open XML
SharePoint and Open XMLSharePoint and Open XML
SharePoint and Open XML
 
Chapter 9 Data Design .pptxInformation Technology Project Management
Chapter 9 Data Design .pptxInformation Technology Project ManagementChapter 9 Data Design .pptxInformation Technology Project Management
Chapter 9 Data Design .pptxInformation Technology Project Management
 
Dbms
DbmsDbms
Dbms
 
michael hamilton legal database design presentation 3 new york
michael hamilton legal database design presentation 3 new yorkmichael hamilton legal database design presentation 3 new york
michael hamilton legal database design presentation 3 new york
 

Plus de Shawn Villaron

Spreadsheet ml subject shared workbooks
Spreadsheet ml subject   shared workbooksSpreadsheet ml subject   shared workbooks
Spreadsheet ml subject shared workbooksShawn Villaron
 
Spreadsheet ml subject query table
Spreadsheet ml subject   query tableSpreadsheet ml subject   query table
Spreadsheet ml subject query tableShawn Villaron
 
Spreadsheet ml subject pivottable
Spreadsheet ml subject   pivottableSpreadsheet ml subject   pivottable
Spreadsheet ml subject pivottableShawn Villaron
 
Spreadsheet ml subject metadata
Spreadsheet ml subject   metadataSpreadsheet ml subject   metadata
Spreadsheet ml subject metadataShawn Villaron
 
Spreadsheet ml subject external links
Spreadsheet ml subject   external linksSpreadsheet ml subject   external links
Spreadsheet ml subject external linksShawn Villaron
 
Spreadsheet ml subject comments
Spreadsheet ml subject   commentsSpreadsheet ml subject   comments
Spreadsheet ml subject commentsShawn Villaron
 
Spreadsheet ml subject calc chain
Spreadsheet ml subject   calc chainSpreadsheet ml subject   calc chain
Spreadsheet ml subject calc chainShawn Villaron
 
Spreadsheet ml overview
Spreadsheet ml overviewSpreadsheet ml overview
Spreadsheet ml overviewShawn Villaron
 
Spreadsheet ml subject xml-mapping
Spreadsheet ml subject   xml-mappingSpreadsheet ml subject   xml-mapping
Spreadsheet ml subject xml-mappingShawn Villaron
 
Spreadsheet ml subject workbook
Spreadsheet ml subject   workbookSpreadsheet ml subject   workbook
Spreadsheet ml subject workbookShawn Villaron
 
Spreadsheet ml subject workbook connections
Spreadsheet ml subject   workbook connectionsSpreadsheet ml subject   workbook connections
Spreadsheet ml subject workbook connectionsShawn Villaron
 
Spreadsheet ml subject volatile dependencies
Spreadsheet ml subject   volatile dependenciesSpreadsheet ml subject   volatile dependencies
Spreadsheet ml subject volatile dependenciesShawn Villaron
 
Spreadsheet ml subject tables
Spreadsheet ml subject   tablesSpreadsheet ml subject   tables
Spreadsheet ml subject tablesShawn Villaron
 
Spreadsheet ml subject styles
Spreadsheet ml subject   stylesSpreadsheet ml subject   styles
Spreadsheet ml subject stylesShawn Villaron
 
Spreadsheet ml subject strings
Spreadsheet ml subject   stringsSpreadsheet ml subject   strings
Spreadsheet ml subject stringsShawn Villaron
 
Spreadsheet ml subject sheet
Spreadsheet ml subject   sheetSpreadsheet ml subject   sheet
Spreadsheet ml subject sheetShawn Villaron
 
3 wordprocessing ml subject - tables
3   wordprocessing ml subject - tables3   wordprocessing ml subject - tables
3 wordprocessing ml subject - tablesShawn Villaron
 
0 wordprocessing ml overview
0   wordprocessing ml overview0   wordprocessing ml overview
0 wordprocessing ml overviewShawn Villaron
 
12 wordprocessing ml subject - annotations
12   wordprocessing ml subject - annotations12   wordprocessing ml subject - annotations
12 wordprocessing ml subject - annotationsShawn Villaron
 
11 wordprocessing ml subject - glossary document
11   wordprocessing ml subject - glossary document11   wordprocessing ml subject - glossary document
11 wordprocessing ml subject - glossary documentShawn Villaron
 

Plus de Shawn Villaron (20)

Spreadsheet ml subject shared workbooks
Spreadsheet ml subject   shared workbooksSpreadsheet ml subject   shared workbooks
Spreadsheet ml subject shared workbooks
 
Spreadsheet ml subject query table
Spreadsheet ml subject   query tableSpreadsheet ml subject   query table
Spreadsheet ml subject query table
 
Spreadsheet ml subject pivottable
Spreadsheet ml subject   pivottableSpreadsheet ml subject   pivottable
Spreadsheet ml subject pivottable
 
Spreadsheet ml subject metadata
Spreadsheet ml subject   metadataSpreadsheet ml subject   metadata
Spreadsheet ml subject metadata
 
Spreadsheet ml subject external links
Spreadsheet ml subject   external linksSpreadsheet ml subject   external links
Spreadsheet ml subject external links
 
Spreadsheet ml subject comments
Spreadsheet ml subject   commentsSpreadsheet ml subject   comments
Spreadsheet ml subject comments
 
Spreadsheet ml subject calc chain
Spreadsheet ml subject   calc chainSpreadsheet ml subject   calc chain
Spreadsheet ml subject calc chain
 
Spreadsheet ml overview
Spreadsheet ml overviewSpreadsheet ml overview
Spreadsheet ml overview
 
Spreadsheet ml subject xml-mapping
Spreadsheet ml subject   xml-mappingSpreadsheet ml subject   xml-mapping
Spreadsheet ml subject xml-mapping
 
Spreadsheet ml subject workbook
Spreadsheet ml subject   workbookSpreadsheet ml subject   workbook
Spreadsheet ml subject workbook
 
Spreadsheet ml subject workbook connections
Spreadsheet ml subject   workbook connectionsSpreadsheet ml subject   workbook connections
Spreadsheet ml subject workbook connections
 
Spreadsheet ml subject volatile dependencies
Spreadsheet ml subject   volatile dependenciesSpreadsheet ml subject   volatile dependencies
Spreadsheet ml subject volatile dependencies
 
Spreadsheet ml subject tables
Spreadsheet ml subject   tablesSpreadsheet ml subject   tables
Spreadsheet ml subject tables
 
Spreadsheet ml subject styles
Spreadsheet ml subject   stylesSpreadsheet ml subject   styles
Spreadsheet ml subject styles
 
Spreadsheet ml subject strings
Spreadsheet ml subject   stringsSpreadsheet ml subject   strings
Spreadsheet ml subject strings
 
Spreadsheet ml subject sheet
Spreadsheet ml subject   sheetSpreadsheet ml subject   sheet
Spreadsheet ml subject sheet
 
3 wordprocessing ml subject - tables
3   wordprocessing ml subject - tables3   wordprocessing ml subject - tables
3 wordprocessing ml subject - tables
 
0 wordprocessing ml overview
0   wordprocessing ml overview0   wordprocessing ml overview
0 wordprocessing ml overview
 
12 wordprocessing ml subject - annotations
12   wordprocessing ml subject - annotations12   wordprocessing ml subject - annotations
12 wordprocessing ml subject - annotations
 
11 wordprocessing ml subject - glossary document
11   wordprocessing ml subject - glossary document11   wordprocessing ml subject - glossary document
11 wordprocessing ml subject - glossary document
 

Dernier

Optimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVOptimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVshikhaohhpro
 
Diamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with PrecisionDiamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with PrecisionSolGuruz
 
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online ☂️
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online  ☂️CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online  ☂️
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online ☂️anilsa9823
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsAlberto González Trastoy
 
Hand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxHand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxbodapatigopi8531
 
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...OnePlan Solutions
 
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...Health
 
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...MyIntelliSource, Inc.
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comFatema Valibhai
 
How To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsHow To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsAndolasoft Inc
 
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdfLearn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdfkalichargn70th171
 
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...panagenda
 
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...ICS
 
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female service
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female serviceCALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female service
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female serviceanilsa9823
 
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Steffen Staab
 
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...kellynguyen01
 
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerHow To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerThousandEyes
 
Right Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsRight Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsJhone kinadey
 

Dernier (20)

Optimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVOptimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTV
 
Diamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with PrecisionDiamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with Precision
 
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICECHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
 
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online ☂️
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online  ☂️CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online  ☂️
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online ☂️
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
 
Hand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxHand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptx
 
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...
 
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
 
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.com
 
Microsoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdfMicrosoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdf
 
How To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsHow To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.js
 
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdfLearn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf
Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf
 
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
 
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
 
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female service
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female serviceCALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female service
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female service
 
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
 
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
 
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerHow To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
 
Right Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsRight Money Management App For Your Financial Goals
Right Money Management App For Your Financial Goals
 

WordprocessingML Mail Merge Components

  • 1. Components of WordprocessingML • Main Document • Paragraphs & Rich Formatting – Runs – Run Content • Tables • Custom Markup • Sections • Styles – Paragraph – Character – Numbering – Table – Document Defaults • Fonts • Numbering • Headers/Footers • Footnotes/Endnotes • Glossary Document • Annotations – Comments – Revisions – Bookmarks • Mail Merge • Document Settings – Web Settings – Compatibility Settings • Fields & Hyperlinks • Odds & Ends (Textboxes, Subdocuments, Extensibility) Ecma/TC45/2006/168
  • 3. Mail Merge • Mail merge refers to a process by which a WordprocessingML document is: – Connected to external data sources – Populated with external data • The information about what data source top connect to, and where to put that data is part of WordprocessingML – The actual merge is a runtime operation
  • 4. Mail Merge Documents • A mail merge document can exist in two states: – A source document, the document that contains the data needed to connect to an external data source for a mail merge – A merged document, the document that contains the data above *plus* the values from and a reference to a single record from that data source • One source document creates many merged documents
  • 5. Source Document Data • The presence of a mailMerge element creates a source document • The data connection information is then stored in the mailMerge element: – Where the external data is located – Type of external data – The query to be run against that data
  • 6. Source Document Data Example Connection String Query Link to Data Source Document ‘Type’
  • 7. Source Document Content • A source document contains the contents of a standard WordprocessingML document with: – Static content such as paragraphs and tables – Mail merge fields that specify the location of the external data within this static document content
  • 8. Source Document Content Example • Standard WordprocessingML document with: – Two mail merge fields for Courtesy Title and Last Name – Static content such as paragraphs and tables
  • 9. Importing External Data • Once we have a source document and the ability to connect to data, we need to do something with it – i.e. perform the mail merge • This is done via mail merge fields, WordprocessingML fields that server as markers for a particular column of external data
  • 10. Importing External Data (cont.) • Mail merge fields can have two types of references to column data: – The column name from the data source – A mapped name (a mapping to a predefined set of merge field names with WordprocessingML) • The latter is present to create one standard set of field names regardless of data source (e.g. to create standard address blocks)
  • 11. Importing External Data Example • Two mail merge fields for Courtesy Title and Last Name • These are mapped fields, so we need to map these predefined names to columns in the data source
  • 12. Field Mappings • The information linking a column to the database column name and a mapped name • A single field mapping contains: – A column number – The field mapping type – The data source’s column name – (optionally) A mapping to a predefined merge field name
  • 13. Field Mappings Example • Looking at the first field map: – The fifth column – Is a database column – Has a database name of Content Model – And a mapping to a predefined name of Job Title
  • 14. Field Mappings Example (cont.) • The resulting mapping allows the content of that fifth column to be referenced by: – A merge field specifying Content Model – A merge field specifying Job Title
  • 15. The Merged Document • A merged document is the result of the mail merge operation against a source document: – The information to connect to the data source – A cache of the contents of a single record – A reference to that record
  • 16. Merged Document Example • Once a source document’s mail merge fields have been mapped to external data, an application may populate the fields with external data • Consider a source document from the previous example – Assume the external data source has one record: Mr. Doe
  • 17. Merged Document Example (cont.) • A document is created containing: – The static contents of the source document – A single record of the external data • In other words, a merged document is generated as a result of the mail merge
  • 19. Appendix • Predefined WordprocessingML merge field names: – Unique Identifier – Courtesy Title – First Name – Middle Name – Last Name – Suffix
  • 20. Appendix (cont.) • Merge field names (cont.) – Nickname – Job Title – Company – Address 1 – Address 2 – City – State
  • 21. Appendix (cont.) • Merge field names (cont.) – Postal Code – Country or Region – Business Phone – Business Fax – Home Phone – Home Fax – E-mail Address
  • 22. Appendix (cont.) • Merge field names (cont.) – Web Page – Spouse Courtesy Title – Spouse First Name – Spouse Last Name – Spouse Nickname – Phonetic Guide for First Name – Phonetic Guide for Last Name
  • 23. Appendix (cont.) • Merge field names (cont.) – Address 3 – Department
  • 24. Disclaimer This presentation is for informational purposes only, and should not be relied upon as a substitute or replacement for Microsoft formal file format documentation, which is available at the following website: https://msdn.microsoft.com/en- us/library/cc313118(v=office.12).aspx. Any views or opinions presented in this material are solely those of the author and do not necessarily represent those of Microsoft. Microsoft disclaims all liability for mistakes or inaccuracies in this presentation.