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Key concepts
Details on documents and templates, the data editors and the Content editor of PLA 3.0. Learn about the position factors and data aggregation features.
Data tables
Data tables in PLA 3.0 act as containers for observation data or referenced data. You use them to configure the display of observation data and to set up automated data flows between PLA 3.0 documents, thus minimizing the need for manual interaction.

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Explore PLA 3.0, its key features and ongoing enhancements, and learn how to log in and register.
User interface
PLA 3.0 supports you in your daily work by providing a set of graphical and textual user interface elements. Learn about the different elements and how to use them efficiently.
Key concepts
Details on documents and templates, the data editors and the Content editor of PLA 3.0. Learn about the position factors and data aggregation features.
- Documents
  PLA 3.0 securely stores all your data within electronic documents. Documents are organized within a database and presented through a folder tree for easy navigation and access. Your data remains complete, accurate, and consistent throughout its life cycle, thus ensuring data integrity.
- Templates
  Use templates to simplify tasks, standardize processes, and improve data security. Define document structures and initial values for documents, and control who can view and edit document sections and individual elements within documents.
- Data tables
  Data tables in PLA 3.0 act as containers for observation data or referenced data. You use them to configure the display of observation data and to set up automated data flows between PLA 3.0 documents, thus minimizing the need for manual interaction.
  - Observation source
    Use the observation source setting to configure how you obtain your observation data. You can enter data manually or aggregate it from other PLA 3.0 documents. The observation source you select influences which data editors you use to enter your observation data.
  - Row order
    Use the row order setting to switch between an ascending and a descending order for your observation data.
  - Column: Boolean
    Use this column to associate each observation with a logical/Boolean value.
  - Column: Date
    Use this column to associate each observation with a date.
  - Column: Date/time
    Use this column to associate each observation with a date and time.
  - Column: Document reference
    Use this column to set up document reference filters. Document reference filters let you decide which of the referenced documents PLA 3.0 can use as source documents.
  - Column: Document title
    Use this column to set a document title.
  - Column: Exclude from analysis
    Use this column to flag technical outlier in the data table.
  - Column: Floating point number
    Use this column to set up floating-point number dataset columns. Dataset columns let you define the parameters you want to aggregate into your target document.
  - Column: Identification
    Use this column to identify specific observations in the report.
  - Column: Integer
    Use this column to associate each observation with a value of integer number format.
  - Column: Memo (multiline text)
    Use this column to associate each observation with a multiline text.
  - Column: Observation group
    Use this column to link individual observations (measurements) to their assay elements. All observations of a group belong to the same assay element.
  - Column: Position factor
    Use this column to set up position factors. Position factors let you define plate layouts for your assays. You can define up to three positions, that is, row, column, and plate.
  - Column: Response value
    Use this column to display the observed response value.
  - Column: Section
    Use this column to set up section filters. Section filters let you decide from which sections within a source document PLA 3.0 can aggregate data.
  - Column: Sequence step
    Use this column to display the sequence step number and the dose value.
  - Column: Technical outlier flag
    Use this column to display flags to mark technical outliers.
  - Column: Text
    Use this column to set up text dataset columns. Dataset columns let you define the parameters you want to aggregate into your target document.
  - Column: Time
    Use this column to associate each observation with a time.
- Position factors
  PLA 3.0 can handle a wide range of plate layouts and is not restricted to any particular format. Position factors in PLA 3.0 support you in defining plate layouts. They let you associate your observation data in PLA 3.0 with its physical location on a plate or rack.
- Data aggregation
  Data aggregation in PLA 3.0 lets you automatically transfer data and results from source to target PLA 3.0 documents, thus supporting complex and compliant operations. Manually entering data in spreadsheets or other programs is not necessary.
Data analysis
Data analysis add-ons offer a wide range of capabilities, ranging from analytical methods over comprehensive analysis to statistical process control. PLA 3.0 also provides a set of add-ons that support and supplement data analysis add-ons.
Data import
Use data acquisition and data import add-ons to import external response values and observation data into PLA 3.0 for further processing and evaluation.
Installation
Details on the deployment, installation, initial and advanced setup of PLA 3.0.
Licensing
Details on the licensing solution of PLA 3.0, the available licensing options, and the activation and management of licenses.
Administration
Details on system administration tasks such as setup and maintenance of databases and add-ons, user accounts, access rights, and migration and update procedures.
Regulatory compliance
PLA 3.0 supports you in achieving compliance with regulations such as ISPE GAMP^® 5 and 21 CFR Part 11. It also provides options to validate PLA 3.0 in your environment.
PDF downloads
Download PDF guides of current and previous framework and add-on versions.
Sample lab
Meet the team at Stegmann Labs, where PLA 3.0 plays an essential role in every step of bioassay management.
Glossary
Find definitions of terms.

Data tables

Data tables in PLA 3.0 act as containers for observation data or referenced data. You use them to configure the display of observation data and to set up automated data flows between PLA 3.0 documents, thus minimizing the need for manual interaction.

Data tables are highly flexible. They serve as integrative elements between the various editors, as shown in the following figure:

Integrative role of data tables in PLA 3.0 — Figure 1. Integrative role of data tables in PLA 3.0

Note: Data tables are only available for document types that handle observation data or referenced data. Document types like Contact, Note, or Equipment do not have data tables.

Data table setup

To set up data tables, you use the Content editor.

This editor displays the data table as a sub-node in the document structure. The name of the sub-node depends on the document type. Quantitative response assay documents, for example, use Observation data. Basic bioassay protocol documents use Reportable values, and Combination of microbial assay documents use Potency data.

Tip: In the Content editor, you can identify data tables by their

icon.

Data table of a Quantitative response assay document — Figure 2. Data table of a Quantitative response assay document

Data tables offer a number of settings that influence the behavior of data editors, allowing you to adapt the handling of observation data in those editors according to your requirements. For details on each settings, see the respective subtopic.

Note: For details on how to work with the Content editor, see the Content editor topic.

Data entry

To enter your observation data, you use the various data editors of PLA 3.0.

Each editor supports different use cases. For example, you use the References editor for setting up data aggregation and the By Position editor for setting up plate layouts. Which editor is available depends on the observation source you select in the data table of the Content editor. For details on each editor, see the respective topic:

Note: For details on how to use references for data aggregation, see the Data aggregation topic.