What's New in Grooper 2021 - Revision history

Dgreenwood at 21:46, 27 August 2025

2025-08-27T21:46:35Z

← Older revision		Revision as of 16:46, 27 August 2025
Line 37:		Line 37:

	:* Document classification - Using the ''Labelset-Based'' '''''Classification Method'''''		:* Document classification - Using the ''Labelset-Based'' '''''Classification Method'''''
	:* Field based data extraction - Primarily using the ''Labeled Value'' ~~'''''~~Extractor ~~Type'''''~~		:* Field based data extraction - Primarily using the ''Labeled Value'' Value Extractor
	:* Tabular data extraction - Primarily using a '''Data Table''' object's ''Tabular Layout'' '''''Extract Method'''''		:* Tabular data extraction - Primarily using a '''Data Table''' object's ''Tabular Layout'' '''''Extract Method'''''
	:* Sectional data extraction - Primarily using a '''Data Section''' object's ''Transaction Detection'' '''''Extract Method'''''		:* Sectional data extraction - Primarily using a '''Data Section''' object's ''Transaction Detection'' '''''Extract Method'''''
Line 89:		Line 89:
	[[File:Value-reader-badge-3.png\|thumb\|150px\|link=Value Reader]]		[[File:Value-reader-badge-3.png\|thumb\|150px\|link=Value Reader]]

	The '''[[Value Reader]]''' is a new extraction object introduced in Grooper 2021 to replace and improve on the '''Data Format''' object. The '''Value Reader''' extractor combines over a dozen multiple ~~extractor types~~ into a single extractor for increased functionality and ease of use.		The '''[[Value Reader]]''' is a new extraction object introduced in Grooper 2021 to replace and improve on the '''Data Format''' object. The '''Value Reader''' extractor combines over a dozen multiple Value Extractors into a single extractor for increased functionality and ease of use.

	It is designed to expand on the extractor functionality of Grooper's regular expression pattern matching capabilities to include newer extraction capabilities, such as extracting values next to OMR (optical mark recognition) checkboxes and barcode values. In previous versions, this functionality was split across multiple objects (or properties of multiple objects). The '''Value Reader''' extractor combines these disparate functionalities into a single extractor object with increased functionality.		It is designed to expand on the extractor functionality of Grooper's regular expression pattern matching capabilities to include newer extraction capabilities, such as extracting values next to OMR (optical mark recognition) checkboxes and barcode values. In previous versions, this functionality was split across multiple objects (or properties of multiple objects). The '''Value Reader''' extractor combines these disparate functionalities into a single extractor object with increased functionality.

	The '''Value Reader''' also adds brand new extraction capabilities through new ~~'''''Extractor Types'''''~~. This includes the ''Labeled Value'' extractor, offering an improvement on ''Key-Value Pair'' collated '''Data Type''' extraction. On top of that, ''Labeled Value'' interacts with Grooper's new Label Set functionality to vastly simplify and improve '''Data Field''' extraction for those projects using the ''Labeling Behavior'' functionality.		The '''Value Reader''' also adds brand new extraction capabilities through new Value Extractors. This includes the ''Labeled Value'' extractor, offering an improvement on ''Key-Value Pair'' collated '''Data Type''' extraction. On top of that, ''Labeled Value'' interacts with Grooper's new Label Set functionality to vastly simplify and improve '''Data Field''' extraction for those projects using the ''Labeling Behavior'' functionality.

	=== Vertical Wrap and Constrained Wrap ===		=== Vertical Wrap and Constrained Wrap ===

Dgreenwood at 19:05, 22 December 2023

2023-12-22T19:05:46Z

← Older revision		Revision as of 14:05, 22 December 2023
Line 187:		Line 187:
	== Improved PDF Splitting ==		== Improved PDF Splitting ==

	Version 2021 makes significant changes to the '''[[Content Action]] Activity'''.		Version 2021 makes significant changes to the '''[[2.90:Content Action]] Activity'''.

	In previous versions of Grooper, multipage PDF documents could have individual child Batch Page objects created from the PDF file attached to the parent '''Batch Folder''', using the '''Content Action Activity''' and the ''Split'' action. This functionality is now performed using a separate '''Activity''' called '''Split Pages'''. The '''Split Pages''' activity offers many new capabilities not previously available.		In previous versions of Grooper, multipage PDF documents could have individual child Batch Page objects created from the PDF file attached to the parent '''Batch Folder''', using the '''Content Action Activity''' and the ''Split'' action. This functionality is now performed using a separate '''Activity''' called '''Split Pages'''. The '''Split Pages''' activity offers many new capabilities not previously available.

Cgarnett: /* Install and Setup Changes */

2021-10-25T15:52:29Z

Install and Setup Changes

← Older revision		Revision as of 10:52, 25 October 2021
Line 182:		Line 182:
	=== Improved Upgrade Process! ===		=== Improved Upgrade Process! ===

	Grooper can now upgrade repositions directly to 2021 from versions, 2.72, 2.80 or 2.90.		Grooper can now upgrade repositions directly to 2021 from versions, 2.70, 2.72, 2.80 or 2.90.
	* Versions older than 2.~~72,~~ ''must'' upgrade to 2.72 before upgrading to 2021.		* Versions older than 2.70 ''must'' upgrade to 2.70 before upgrading to 2021.

	== Improved PDF Splitting ==		== Improved PDF Splitting ==

Dgreenwood at 15:21, 23 September 2021

2021-09-23T15:21:20Z

← Older revision		Revision as of 10:21, 23 September 2021
Line 22:		Line 22:
	The following Behavior Types are introduced in 2021:		The following Behavior Types are introduced in 2021:

	* '''''Import Behavior'''''		:* '''''Import Behavior'''''
	* '''''Export Behavior'''''		:* '''''Export Behavior'''''
	* '''''Labeling Behavior'''''		:* '''''Labeling Behavior'''''
	* '''''PDF Data Mapping'''''		:* '''''PDF Data Mapping'''''
	* '''''Text Rendering'''''		:* '''''Text Rendering'''''

	<br clear=all>		<br clear=all>
Line 36:		Line 36:
	The ''[[Labeling Behavior]]'' functionality represents a huge change in how document content can be modeled and collected for structured and semi-structured document sets. It capitalizes on the utility labels provide to understand a document and its data. Grooper collects and uses "Label Sets" for each '''Document Type''' for a variety of document processing purposes, including:		The ''[[Labeling Behavior]]'' functionality represents a huge change in how document content can be modeled and collected for structured and semi-structured document sets. It capitalizes on the utility labels provide to understand a document and its data. Grooper collects and uses "Label Sets" for each '''Document Type''' for a variety of document processing purposes, including:

	* Document classification - Using the ''Labelset-Based'' '''''Classification Method'''''		:* Document classification - Using the ''Labelset-Based'' '''''Classification Method'''''
	* Field based data extraction - Primarily using the ''Labeled Value'' '''''Extractor Type'''''		:* Field based data extraction - Primarily using the ''Labeled Value'' '''''Extractor Type'''''
	* Tabular data extraction - Primarily using a '''Data Table''' object's ''Tabular Layout'' '''''Extract Method'''''		:* Tabular data extraction - Primarily using a '''Data Table''' object's ''Tabular Layout'' '''''Extract Method'''''
	* Sectional data extraction - Primarily using a '''Data Section''' object's ''Transaction Detection'' '''''Extract Method'''''		:* Sectional data extraction - Primarily using a '''Data Section''' object's ''Transaction Detection'' '''''Extract Method'''''

	"Label Sets" offer vast improvements to these areas, both simplifying setup and allowing for quicker onboarding of new '''Document Types''' for structured and semi-structures forms.		"Label Sets" offer vast improvements to these areas, both simplifying setup and allowing for quicker onboarding of new '''Document Types''' for structured and semi-structures forms.
Line 55:		Line 55:
	The ''PDF Data Mapping'' functionality includes the ability to embed PDFs with the following data:		The ''PDF Data Mapping'' functionality includes the ability to embed PDFs with the following data:

	*'''''Metadata'''''		:*'''''Metadata'''''
	*'''''Bookmarks'''''		:*'''''Bookmarks'''''
	*'''''Annotations'''''		:*'''''Annotations'''''

	<br clear=all>		<br clear=all>
Line 98:		Line 98:

	Part of Grooper's switch to the '''Value Reader''' object allows for simplified extraction of data wrapping multiple lines, in certain situations.		Part of Grooper's switch to the '''Value Reader''' object allows for simplified extraction of data wrapping multiple lines, in certain situations.
	*[[Vertical Wrap]] for easier stacked label matching.
	*[[Constrained Wrap]] for easier pattern matching for data constrained in a box (think table cells).		:*[[Vertical Wrap]] for easier stacked label matching.
			:*[[Constrained Wrap]] for easier pattern matching for data constrained in a box (think table cells).

	=== OMR Improvements ===		=== OMR Improvements ===
Line 118:		Line 119:

	2021 also introduces three brand new table extraction methods.		2021 also introduces three brand new table extraction methods.

	* ''[[Tabular Layout]]''		* ''[[Tabular Layout]]''
	** This method brings the most advanced improvements to table extraction to date. Building on the best parts of ''Header-Value'' and ''Infer Grid'', this method returns highly accurate results with simplified initial setup but enough configurability to target a wide variety of table structures.		** This method brings the most advanced improvements to table extraction to date. Building on the best parts of ''Header-Value'' and ''Infer Grid'', this method returns highly accurate results with simplified initial setup but enough configurability to target a wide variety of table structures.
Line 175:		Line 177:
	Please visit the following articles for a more detailed explaination of Grooper Config and the current Grooper instalation and setup instructions:		Please visit the following articles for a more detailed explaination of Grooper Config and the current Grooper instalation and setup instructions:

	* [[Grooper Config]]		:* [[Grooper Config]]
	* [[Install and Setup]]		:* [[Install and Setup]]

	=== Improved Upgrade Process! ===		=== Improved Upgrade Process! ===
Line 195:		Line 197:
	* Document Viewer improvements		* Document Viewer improvements
	* Text file processing improvements		* Text file processing improvements
			* Re-organization of the '''Global Resources''' folder.
			** The '''Global Resources''' folder now houses all globally accessible Grooper objects, including '''Data Types''', '''CMIS Connections''', and '''Data Connections'''.
			** Furthermore, you can organize these assets however you see fit by creating sub folders. For example, '''IP Profiles''' can exist in any folder in the '''Global Resources''' folder, not ''just'' an '''IP Profiles''' sub-folder.

Dgreenwood at 15:08, 23 September 2021

2021-09-23T15:08:08Z

← Older revision		Revision as of 10:08, 23 September 2021
Line 14:		Line 14:
	== Introducing... Behaviors! ==		== Introducing... Behaviors! ==

	[[File:behaviors-badge.png\|thumb\|150px]]		[[File:behaviors-badge-3.png\|thumb\|150px\|link=Behaviors]]

	'''''[[Behaviors]]''''' are a new set of features designed to centralize the '''Content Model''' as the main hub controlling various aspects of document processing. '''''Behaviors''''' are born of the idea that consolidating the the flow of document data to the objects most relevant to its collection and delivery makes for a more streamlined and effective Grooper experience.		'''''[[Behaviors]]''''' are a new set of features designed to centralize the '''Content Model''' as the main hub controlling various aspects of document processing. '''''Behaviors''''' are born of the idea that consolidating the the flow of document data to the objects most relevant to its collection and delivery makes for a more streamlined and effective Grooper experience.
Line 32:		Line 32:
	== Introducing... Label Sets! ==		== Introducing... Label Sets! ==

	[[File:label-sets-badge.png\|thumb\|150px]]		[[File:label-sets-badge-3.png\|thumb\|150px\|link=Labeling Behavior]]

	The ''[[Labeling Behavior]]'' functionality represents a huge change in how document content can be modeled and collected for structured and semi-structured document sets. It capitalizes on the utility labels provide to understand a document and its data. Grooper collects and uses "Label Sets" for each '''Document Type''' for a variety of document processing purposes, including:		The ''[[Labeling Behavior]]'' functionality represents a huge change in how document content can be modeled and collected for structured and semi-structured document sets. It capitalizes on the utility labels provide to understand a document and its data. Grooper collects and uses "Label Sets" for each '''Document Type''' for a variety of document processing purposes, including:
Line 47:		Line 47:
	== Introducing... PDF Data Mapping! ==		== Introducing... PDF Data Mapping! ==

	[[File:smart-pdf-badge.png\|thumb\|150px]]		[[File:smart-pdf-badge-3.png\|thumb\|150px\|link=PDF Data Mapping]]

	The ''[[PDF Data Mapping]]'' functionality is part of the foundation for Grooper's "Smart PDF" architecture. The "Smart PDF" architecture's goal is to unify document content into a single source. Too often it is the case document content is divided in two, with the image-based and text content being represented as a PDF file and the data content living in a database or other content management platform.		The ''[[PDF Data Mapping]]'' functionality is part of the foundation for Grooper's "Smart PDF" architecture. The "Smart PDF" architecture's goal is to unify document content into a single source. Too often it is the case document content is divided in two, with the image-based and text content being represented as a PDF file and the data content living in a database or other content management platform.
Line 63:		Line 63:
	== Introducing... Data Rules! ==		== Introducing... Data Rules! ==

	[[File:rules-engine-badge.png\|thumb\|150px]]		[[File:rules-engine-badge-3.png\|thumb\|150px\|link=Data Rule]]

	The '''[[Data Rule]]''' is a new object available in Grooper 2021. '''Data Rules''' allow for complex validation and manipulation of '''Data Elements''' in a '''Data Model'''. This allows users to create a conditional hierarchy of actions to take if certain conditions are met. This includes clearing, copying, appending, parsing and calculating values based on a series of expression based conditions. '''Data Rules''' expand on simpler validation and calculation methods available to '''Data Element''' objects, and allow for more simplified setup and net new capabilities for more complicated data normalization projects.		The '''[[Data Rule]]''' is a new object available in Grooper 2021. '''Data Rules''' allow for complex validation and manipulation of '''Data Elements''' in a '''Data Model'''. This allows users to create a conditional hierarchy of actions to take if certain conditions are met. This includes clearing, copying, appending, parsing and calculating values based on a series of expression based conditions. '''Data Rules''' expand on simpler validation and calculation methods available to '''Data Element''' objects, and allow for more simplified setup and net new capabilities for more complicated data normalization projects.
Line 75:		Line 75:
	== Introducing... API! ==		== Introducing... API! ==

	[[File:api-badge.png\|thumb\|150px]]		[[File:api-badge-3.png\|thumb\|150px]]

	Beginning in 2021, Grooper offers a RESTful Document Ingestion API. The document ingestion API provides the ability to create and populate batches, and the ability to monitor the status of batch processes, and retrieve results. It allows users to create dashboards or portals that interface with existing processes, including allowing them to build portals that feed documents into a Grooper process, or dashboards that display, and change extracted values.		Beginning in 2021, Grooper offers a RESTful Document Ingestion API. The document ingestion API provides the ability to create and populate batches, and the ability to monitor the status of batch processes, and retrieve results. It allows users to create dashboards or portals that interface with existing processes, including allowing them to build portals that feed documents into a Grooper process, or dashboards that display, and change extracted values.
Line 87:		Line 87:
	=== Goodbye Data Formats... Hello Value Reader! ===		=== Goodbye Data Formats... Hello Value Reader! ===

	[[File:~~Document_viewer_00~~.png\|thumb\|150px]]		[[File:Value-reader-badge-3.png\|thumb\|150px\|link=Value Reader]]

	The '''[[Value Reader]]''' is a new extraction object introduced in Grooper 2021 to replace and improve on the '''Data Format''' object. The '''Value Reader''' extractor combines over a dozen multiple extractor types into a single extractor for increased functionality and ease of use.		The '''[[Value Reader]]''' is a new extraction object introduced in Grooper 2021 to replace and improve on the '''Data Format''' object. The '''Value Reader''' extractor combines over a dozen multiple extractor types into a single extractor for increased functionality and ease of use.

Dgreenwood at 15:37, 22 September 2021

2021-09-22T15:37:23Z

← Older revision		Revision as of 10:37, 22 September 2021
Line 14:		Line 14:
	== Introducing... Behaviors! ==		== Introducing... Behaviors! ==

	[[File:behaviors-badge.png\|thumb\|~~175px~~]]		[[File:behaviors-badge.png\|thumb\|150px]]

	'''''[[Behaviors]]''''' are a new set of features designed to centralize the '''Content Model''' as the main hub controlling various aspects of document processing. '''''Behaviors''''' are born of the idea that consolidating the the flow of document data to the objects most relevant to its collection and delivery makes for a more streamlined and effective Grooper experience.		'''''[[Behaviors]]''''' are a new set of features designed to centralize the '''Content Model''' as the main hub controlling various aspects of document processing. '''''Behaviors''''' are born of the idea that consolidating the the flow of document data to the objects most relevant to its collection and delivery makes for a more streamlined and effective Grooper experience.
Line 27:		Line 27:
	* '''''PDF Data Mapping'''''		* '''''PDF Data Mapping'''''
	* '''''Text Rendering'''''		* '''''Text Rendering'''''

			<br clear=all>

	== Introducing... Label Sets! ==		== Introducing... Label Sets! ==

			[[File:label-sets-badge.png\|thumb\|150px]]

	The ''[[Labeling Behavior]]'' functionality represents a huge change in how document content can be modeled and collected for structured and semi-structured document sets. It capitalizes on the utility labels provide to understand a document and its data. Grooper collects and uses "Label Sets" for each '''Document Type''' for a variety of document processing purposes, including:		The ''[[Labeling Behavior]]'' functionality represents a huge change in how document content can be modeled and collected for structured and semi-structured document sets. It capitalizes on the utility labels provide to understand a document and its data. Grooper collects and uses "Label Sets" for each '''Document Type''' for a variety of document processing purposes, including:
Line 38:		Line 42:

	"Label Sets" offer vast improvements to these areas, both simplifying setup and allowing for quicker onboarding of new '''Document Types''' for structured and semi-structures forms.		"Label Sets" offer vast improvements to these areas, both simplifying setup and allowing for quicker onboarding of new '''Document Types''' for structured and semi-structures forms.

			<br clear=all>

	== Introducing... PDF Data Mapping! ==		== Introducing... PDF Data Mapping! ==

			[[File:smart-pdf-badge.png\|thumb\|150px]]

	The ''[[PDF Data Mapping]]'' functionality is part of the foundation for Grooper's "Smart PDF" architecture. The "Smart PDF" architecture's goal is to unify document content into a single source. Too often it is the case document content is divided in two, with the image-based and text content being represented as a PDF file and the data content living in a database or other content management platform.		The ''[[PDF Data Mapping]]'' functionality is part of the foundation for Grooper's "Smart PDF" architecture. The "Smart PDF" architecture's goal is to unify document content into a single source. Too often it is the case document content is divided in two, with the image-based and text content being represented as a PDF file and the data content living in a database or other content management platform.
Line 47:		Line 55:
	The ''PDF Data Mapping'' functionality includes the ability to embed PDFs with the following data:		The ''PDF Data Mapping'' functionality includes the ability to embed PDFs with the following data:

	* '''''Metadata'''''		*'''''Metadata'''''
	* '''''Bookmarks'''''		*'''''Bookmarks'''''
	* '''''Annotations'''''		*'''''Annotations'''''

			<br clear=all>

	== Introducing... Data Rules! ==		== Introducing... Data Rules! ==

			[[File:rules-engine-badge.png\|thumb\|150px]]

	The '''[[Data Rule]]''' is a new object available in Grooper 2021. '''Data Rules''' allow for complex validation and manipulation of '''Data Elements''' in a '''Data Model'''. This allows users to create a conditional hierarchy of actions to take if certain conditions are met. This includes clearing, copying, appending, parsing and calculating values based on a series of expression based conditions. '''Data Rules''' expand on simpler validation and calculation methods available to '''Data Element''' objects, and allow for more simplified setup and net new capabilities for more complicated data normalization projects.		The '''[[Data Rule]]''' is a new object available in Grooper 2021. '''Data Rules''' allow for complex validation and manipulation of '''Data Elements''' in a '''Data Model'''. This allows users to create a conditional hierarchy of actions to take if certain conditions are met. This includes clearing, copying, appending, parsing and calculating values based on a series of expression based conditions. '''Data Rules''' expand on simpler validation and calculation methods available to '''Data Element''' objects, and allow for more simplified setup and net new capabilities for more complicated data normalization projects.

	There are also two new '''Batch Processing Activities''' that apply '''Data Rules''' as well:		There are also two new '''Batch Processing Activities''' that apply '''Data Rules''' as well:
	* '''Apply Rules'''		:* '''Apply Rules'''
	* '''Convert Data'''		:* '''Convert Data'''

			<br clear=all>

	== Introducing... API! ==		== Introducing... API! ==

			[[File:api-badge.png\|thumb\|150px]]

	Beginning in 2021, Grooper offers a RESTful Document Ingestion API. The document ingestion API provides the ability to create and populate batches, and the ability to monitor the status of batch processes, and retrieve results. It allows users to create dashboards or portals that interface with existing processes, including allowing them to build portals that feed documents into a Grooper process, or dashboards that display, and change extracted values.		Beginning in 2021, Grooper offers a RESTful Document Ingestion API. The document ingestion API provides the ability to create and populate batches, and the ability to monitor the status of batch processes, and retrieve results. It allows users to create dashboards or portals that interface with existing processes, including allowing them to build portals that feed documents into a Grooper process, or dashboards that display, and change extracted values.

	The API has some other capabilities, such as the ability to ingest compressed archives of Grooper notes (which could assist in automation of new repository population) and the ability to query certain pieces of information from the repository.		The API has some other capabilities, such as the ability to ingest compressed archives of Grooper notes (which could assist in automation of new repository population) and the ability to query certain pieces of information from the repository.

			<br clear=all>

	== Data Extraction Improvements ==		== Data Extraction Improvements ==

Dgreenwood: /* Introducing... Behaviors! */

2021-09-22T15:25:00Z

Introducing... Behaviors!

← Older revision		Revision as of 10:25, 22 September 2021
Line 14:		Line 14:
	== Introducing... Behaviors! ==		== Introducing... Behaviors! ==

	[[File:~~Behaviours_00~~.png\|thumb\|175px]]		[[File:behaviors-badge.png\|thumb\|175px]]

	'''''[[Behaviors]]''''' are a new set of features designed to centralize the '''Content Model''' as the main hub controlling various aspects of document processing. '''''Behaviors''''' are born of the idea that consolidating the the flow of document data to the objects most relevant to its collection and delivery makes for a more streamlined and effective Grooper experience.		'''''[[Behaviors]]''''' are a new set of features designed to centralize the '''Content Model''' as the main hub controlling various aspects of document processing. '''''Behaviors''''' are born of the idea that consolidating the the flow of document data to the objects most relevant to its collection and delivery makes for a more streamlined and effective Grooper experience.

Dgreenwood: /* Introducing... API! */

2021-09-02T16:58:15Z

Introducing... API!

← Older revision		Revision as of 11:58, 2 September 2021
Line 63:		Line 63:
	Beginning in 2021, Grooper offers a RESTful Document Ingestion API. The document ingestion API provides the ability to create and populate batches, and the ability to monitor the status of batch processes, and retrieve results. It allows users to create dashboards or portals that interface with existing processes, including allowing them to build portals that feed documents into a Grooper process, or dashboards that display, and change extracted values.		Beginning in 2021, Grooper offers a RESTful Document Ingestion API. The document ingestion API provides the ability to create and populate batches, and the ability to monitor the status of batch processes, and retrieve results. It allows users to create dashboards or portals that interface with existing processes, including allowing them to build portals that feed documents into a Grooper process, or dashboards that display, and change extracted values.

	The API ~~Has~~ some other capabilities, such as the ability to ingest compressed archives of Grooper notes (which could assist in automation of new repository population) and the ability to query certain pieces of information from the repository.		The API has some other capabilities, such as the ability to ingest compressed archives of Grooper notes (which could assist in automation of new repository population) and the ability to query certain pieces of information from the repository.

	== Data Extraction Improvements ==		== Data Extraction Improvements ==

Dgreenwood at 14:28, 2 September 2021

2021-09-02T14:28:31Z

Show changes

Dgreenwood: /* Introducing... PDF Data Mapping! */

2021-09-02T13:54:18Z

Introducing... PDF Data Mapping!

← Older revision		Revision as of 08:54, 2 September 2021
Line 43:		Line 43:
	The ''[[PDF Data Mapping]]'' functionality is part of the foundation for Grooper's "Smart PDF" architecture. The "Smart PDF" architecture's goal is to unify document content into a single source. Too often it is the case document content is divided in two, with the image-based and text content being represented as a PDF file and the data content living in a database or other content management platform.		The ''[[PDF Data Mapping]]'' functionality is part of the foundation for Grooper's "Smart PDF" architecture. The "Smart PDF" architecture's goal is to unify document content into a single source. Too often it is the case document content is divided in two, with the image-based and text content being represented as a PDF file and the data content living in a database or other content management platform.

	''PDF Data Mapping'' allows Grooper to store data content directly to the PDF itself, including separation and classification data as well as Data Fields from a Data Model. This way, even if you do store document data in a database, the document itself retains all the information Grooper collected inside the PDF itself as well.		''PDF Data Mapping'' allows Grooper to store data content directly to the PDF itself, including separation and classification data as well as '''Data Fields''' from a '''Data Model''', through document metadata. This way, even if you do store document data in a database, the document itself retains all the information Grooper collected inside the PDF itself as well.

	The PDF Data Mapping functionality includes the ability to embed PDFs with the following data:		The ''PDF Data Mapping'' functionality includes the ability to embed PDFs with the following data:

	* '''''Metadata'''''		* '''''Metadata'''''