About access and filters

To properly view data in the Audit Trail Dashboard, you must have access to the Subject Form Items dataset. For more information see Permissions to access Oracle Clinical One Analytics datasets.

Additionally, some charts can be used as filters. Look for the filter icon () to the left of the visualization chart. Click on any element of the chart with filter interactivity to filter out the remaining visualizations according to the selected data. To reverse selection on the chart, click on any white space within it or use the undo button () in the upper right corner of the screen.

Note:

If the selected filters point to data not present on another chart, No Data Found will be displayed.

Reports

Data Operations Summary

Use case: to review the volume of data across studies, sites, subjects, visits, forms, and Oracle Clinical One Platform objects, as well as the distribution of data operations.

Insights:

• Overall key performance indicator for data volume.
• Identify high volume data operations across studies and sites.
• Data operations breakdown across studies and sites, based on operation type.

Visualizations:

Table 4-1 Data Operations Summary visualizations

Title	Description	Interactivity
Study Count	Represents the total count of studies. Type: Tile chart. Count: Studies with distinct STUDY_WID.	Filtered data.
Site Count	Represents the total count of sites. Type: Tile chart. Count: Sites with distinct SITE_WID.	Filtered data.
Subject Count	Represents the total count of subjects. Type: Tile chart. Count: Subjects with distinct SUBJECT_WID.	Filtered data.
Visit Count	Represents the total count of visits. Type: Tile chart. Count: Visits with distinct EVENT_WID.	Filtered data.
Form Count	Represents the total count of forms. Type: Tile chart. Count: Forms with distinct FORM_WID.	Filtered data.
Item Count	Represents the total count of items. Type: Tile chart. Count: Items with distinct ITEM_WID.	Filtered data.
Created Actions	Represents the total count of created items. Type: Tile chart. Count: Actions with an OPERATION_TYPE of 'CREATED'.	Filtered data.
Modified Actions	Represents the total count of modified items. Type: Tile chart. Count: Actions with an OPERATION_TYPE of 'MODIFIED'.	Filtered data.
Removed Actions	Represents the total count of removed items. Type: Tile chart. Count: Actions with an OPERATION_TYPE of 'REMOVED'.	Filtered data.
Cleared Actions	Represents the total count of cleared items. Type: Tile chart. Count: Actions with an OPERATION_TYPE of 'CLEARED'.	Filtered data.
Data operations metrics	Represents the count of subjects, visits, forms, items, created items, modified items, removed items as well as cleared items, all against their respective studies, sites, and countries. Type: Pivot chart. Columns: STUDY_TITLE SITE_NAME COUNTRY_NAME Subject Count Visit Count Form Count Item Count Created Count Modified Actions Removed Actions Cleared Actions	Filtered data.
Data operations by site and study	Represents operation counts for different sites in a study. Type: Combo chart X-Axis: Item counts. Different colors represent a different item operation count: Created Item Count Modified Item Count Removed Item Count Cleared Item Count Y-Axis: SITE_NAME.	Filtered data.

Data Operations Evolution

Use case: to review the volume of data modifications by country, site, subject, user, visit, form, and items.

Insights:

• Large volumes of data modifications may indicate the necessity for an investigation into data integrity.
• Overview of user performance by country, site, subject, user, visit, form, or items.

Visualizations:

Table 4-2 Data Operations Evolution visualizations

Title	Description	Interactivity
Data Operations Evolution	Represents the totality of data operations from the inception of the study. Type: Combo chart. X-Axis: Operation Month. Y-Axis: Total Created Item Count Total Modified Item Count Total Removed Item Count Total Cleared Item Count The chart represents Total Created Item Count with a line, and Total Modified, Removed, and Cleared Item Counts with separate bars of different colors.	Filtered data.
Data Operations Created vs Verified	Represents a comparison between the volumes of created and verified data, over a set interval. Type: Combo chart. X-Axis: Operation Month. Y-Axis: Total Created Item Count and Total Verified Item Count, each displayed as lines of different colors.	Filtered data.
Data Operations Updated vs Unverified	Represents a comparison between the total volumes of updated and of unverified data operations from the inception of the study. Type: Combo chart. X-Axis: Operation Month Y-Axis: Total Item Updates Count (Modified + Cleared + Removed) and Total Unverified Count, each displayed as lines of different colors.	Filtered data.
Data Operations Evolution Details	Represents the total count of created, modified, removed, and cleared items against study, country, and site. Type: Pivot chart Columns: STUDY_TITLE COUNTRY_NAME SITE_NAME A monthly breakdown of each of the following metrics: Total Created Count Total Modified Count Total Removed Count Total Cleared Count	Filtered data.

Data Operations Analysis

Use cases: to review the volume of data and data operations by country, site, user, visit, and form.

Insights:

• Large volumes of data operations may indicate the necessity for oversight of changes to critical data.
• Can help proactively bring process improvements based on trends.

Visualizations:

Table 4-3 Data Operations Analysis visualizations

Title	Description	Interactivity
Data volume by country	Represents the total volume of data operations on a country by country basis. Type: Heat map.	This chart operates as a filter for all other charts on the page.
Operations by site	Represents the total number of operations across each site. Type: Horizontal stacked bar chart. X-Axis: Represents the item count by site for different operations with different colors: Create Modify Remove Clear Y-Axis: SITE_NAME.	Filtered data.
Operations by user	Represents the total number of operations each user has performed. Type: Horizontal stacked bar chart. X-Axis: Represents with different colors the item count by user for different operations: Create Modify Remove Clear Y-Axis: USER_NAME	This chart can be used as a filter for other charts on the dashboard.
Operations by study role	Represents the total number of operations all users of a particular study role have performed. Type: Horizontal stacked bar chart. X-Axis: Represents with different colors the item count by study role for different operations: Create Modify Remove Clear Y-Axis: CURRENT_STUDY_ROLE	This chart can be used as a filter for other charts on the dashboard.
Operations by visit	Represents the total number of operations performed for each of a study's visits. Type: Horizontal stacked bar chart. X-Axis: Represents with different colors the item count by visit for different operations: Create Modify Remove Clear Y-Axis: EVENT_NAME.	This chart can be used as a filter for other charts on the dashboard.
Operations by form	Represents the total number of operations performed for each of a study's forms. Type: Horizontal stacked bar chart. X-Axis: Represents with different colors the Item count by form for different operations: Create Modify Remove Clear Y-Axis: FORM_NAME.	This chart can be used as a filter for other charts on the dashboard.
Data updates where item has query	Represents the totality of operations for which a query has been raised. Type: Vertical stacked bar chart. X-Axis: OPERATION_TYPE Y-Axis: Total items and items with queries counts represented as bars of different colors: Total Item Count Has Query Count	This chart can be used as a filter for other charts on the dashboard.
Data changes by reason	Represents reasons for data changes in accordance with how commonly they have been used. Type: Tab cloud chart. The chart represents REASON items as individual elements, the colors of which change in accordance with their associated OPERATION_TYPE.	This chart can be used as a filter for other charts on the dashboard.

Data Modifications Analysis

Use cases: to review the volume of data modifications by country, site, subject, user, visit, form, and items.

Insights:

• Large volumes of data modifications may indicate the necessity for an investigation into data integrity.
• Can help with improving the performance of users.

Visualizations:

Table 4-4 Data Modifications Analysis

Title	Description	Interactivity
Data modifications by top 5 countries	Represents the five most active countries when it comes to the volume of data modifications. Type: Stacked bar chart. X-Axis: COUNTRY_NAME. Y-Axis: Modified actions count. Different colors represent item count for different modification operations.	This chart can be used as a filter for other charts on the dashboard.
Data modifications by top 5 sites	Represents the five most active sites when it comes to the volume of data modifications. Type: Horizontal stacked bar chart. X-Axis: Modified actions count. Different colors represent item count for different modification operations. Y-Axis: SITE_NAME.	This chart can be used as a filter for other charts on the dashboard.
Data modifications by top 5 users	Represents the five most active users when it comes to the volume of data modifications. Type: Horizontal stacked bar chart. X-Axis: Modified Actions count. Different colors represent item count for different modification operations. Y-Axis: USER_NAME.	This chart can be used as a filter for other charts on the dashboard.
Data modifications by top 5 subjects	Represents five subjects the data of which has been most modified. Type: Stacked bar chart. X-Axis: SUBJECT_NUMBER. Y-Axis: Modified actions count. Different colors represent item count for different modification operations.	This chart can be used as a filter for other charts on the dashboard.
Data modifications by top 5 forms	Represents five forms for which the most data modification operations have been recorded. Type: Horizontal stacked bar chart. X-Axis: Modified actions count. Different colors represent item count for different modification operations. Y-Axis: FORM_NAME.	This chart can be used as a filter for other charts on the dashboard.
Data modifications by top 5 items	Represents five items for which the most data modification operations have been recorded. Type: Horizontal stacked bar chart. X-Axis: Modified actions count. Different colors represent item count for different modification operations. Y-Axis: ITEM_NAME	This chart can be used as a filter for other charts on the dashboard.
Subject Audit Trail Data	Lists all of the creation, modification, and removal operations performed as part of a study. Type: Table chart. Columns: STUDY_TITLE SITE_NAME COUNTRY_NAME SUBJECT_NUMBER EVENT_TITLE FORM_NAME Form Sequence Value VERSION_START OPERATION_TYPE USER_NAME REASON COMMENTS IS_CURRENT The chart represents the nature of the operation using different colors.	Filtered data.

Form Data Modifications Analysis

Use cases: to review the volume of data modifications by country, site, subject, user, visit, form, and items.

Insights:

• Large volumes of data modifications may indicate the necessity for an investigation into data integrity.
• Can help with improving the performance of users.

Visualizations:

Table 4-5 Form Data Modifications Analysis visualizations

Title	Description	Interactivity
Form Modification Volume	Represents the total volume of modification, removal, and clearance actions performed for a study's forms. Type: Pivot chart. Columns: FORM_NAME Modified Actions Cleared Actions Removed Actions This chart represents the volume of operations using color-coded cells, with the forms with the most performed actions appearing at the top. Color shades are also used to represent the volumes of data operations.	This chart can be used as a filter for the Modifications by Visit, Form & Item chart from this dashboard.
Modification by Visit, Form & Item	Represents a study's forms and the actions of modification performed on their associated data, as well as their volume. Type: Tree Map chart Represents FORM_NAME, EVENT_TITLE, and ITEM_NAME as categories, as well as the count of Modified Actions. The volume of each operation is also represented using color shades.	Filtered data.

Subject Audit Trail Data

Use cases: to review the volume of data modifications by country, site, subject, user, visit, form, and items.

Insights:

• Large volumes of data modifications may indicate the necessity for an investigation into data integrity.
• Can help with improving the performance of users.

Visualizations:

Table 4-6 Subject Audit Trail Data visualizations

Title	Description	Interactivity
Subject Audit Trail Data	Lists all of the creation, modification, and removal operations performed as part of a study. Type: Table chart. Columns: STUDY_TITLE SITE_NAME COUNTRY_NAME SUBJECT_NUMBER EVENT_TITLE FORM_NAME Form Sequence Value VERSION_START OPERATION_TYPE USER_NAME REASON COMMENTS IS_CURRENT The chart represents the nature of the operation using different colors.	Filtered data.