Activity Summary
Visualize and analyze activity patterns across projects, tables, personnel, and time periods with customizable charts and data aggregation
Specs
Version
0.1.0 (updated on 2025-04-27)
Developer
Labii Inc.
Type
Section
Support Configuration
Yes
Overview
The Activity Summary widget provides comprehensive visualization and analysis of activity patterns across your laboratory data. By automatically aggregating activity counts, this widget enables laboratory professionals to track system usage, analyze team engagement, and understand workflow trends. Users can configure dynamic queries to filter activities by projects, tables, personnel, activity types, and date ranges, then visualize results through multiple chart types including bar charts, line graphs, pie charts, and radar plots.
Use Cases
Usage Tracking: Monitor activity rates by personnel to assess team engagement and system adoption
Project Analytics: Compare activity volumes across different projects to identify active research areas and collaboration hotspots
Temporal Analysis: Track activity trends over time (daily, weekly, monthly, yearly) to identify usage patterns and peak periods
Activity Type Distribution: Visualize the distribution of activity types (creates, edits, views, deletions) to understand workflow behavior
Performance Reporting: Generate visual reports for management reviews, system audits, and usage analytics
Resource Planning: Analyze historical activity patterns to forecast system load and resource requirements
Compliance Monitoring: Track user actions and documentation completeness across projects and personnel
Audit Support: Provide aggregated activity overviews to complement detailed audit trail records
Interface
Read-only View
The read-only view displays the configured chart with your aggregated activity data. The chart presents data according to your selected grouping method (projects, tables, personnel, date, or activity type) and value type (activity count).
Data Display: Interactive chart showing aggregated activity data with labeled axes and legend
Chart Interactions: Hover over data points or segments to view detailed values and labels
Visual Clarity: Color-coded groupings make it easy to distinguish between different categories
Legend: Clear identification of each data series or category represented in the chart
Edit View
The edit view provides comprehensive configuration options for building custom queries and defining chart parameters. This interface allows you to specify data filters, grouping methods, and visualization styles.
Query Builder: Interface for constructing data filters using tables, projects, personnel, activity types, and dates
Chart Configuration: Options to define grouping methods and value calculation types
Build Actions: Button to generate or regenerate the chart based on current configuration
Preview: Immediate chart rendering after clicking the BUILD CHART button
Chart Type Selection: Dropdown or button interface to switch between different visualization types
Configuration
Initial Setup
Add the Activity Summary widget to your section by clicking Add Widget and selecting Activity Summary from the Report category
Click the Edit button or widget settings icon to enter configuration mode
Configure your data query parameters to define which activities to include in the analysis
Build Query Settings
Configure the following parameters to filter which activities are included in your summary:
Required Settings
No settings are strictly required — leaving filters empty includes all accessible activity data.
Optional Settings
Tables: Select one or multiple tables to include in the analysis. If empty, activities from all tables are included
Projects: Select one or multiple projects to filter activities. If empty, all projects you have access to are included
Personnel: Select one or multiple team members to filter activities by actor. If empty, all personnel are included
Start Date: Set the earliest activity date for included records. Leave empty to include all activities from the beginning
End Date: Set the latest activity date for included records. Leave empty to include all activities through the present
Query: Enter a custom query string to apply advanced filtering logic to the activity selection
Query filters are combined using AND logic — activities must meet all specified criteria to be included in the summary.
Build Chart Settings
Configure how your filtered activity data is grouped and calculated:
Group By Options
Select how to organize your data:
Projects: Group activities by project to compare engagement and volume across different research initiatives
Tables: Group activities by table type to analyze which data types generate the most activity
Personnel: Group activities by team member to track individual contributions and system usage
Date: Group activities by time periods to identify temporal trends
Time Unit: Select the granularity (Days, Weeks, Months, or Years)
Time Range: Specify the duration for date segmentation
Value Options
Define what the chart values represent:
Activity Count: Display the number of activities in each group (the primary option for activity analysis)
Choose your Group By option to define how activity data should be organized
Select your Value type to determine what the chart measures
Click BUILD CHART to generate the visualization with your configuration
Start with Activity Count and Personnel grouping for a quick overview of your team's engagement and system usage patterns.
Advanced Configuration
For complex analytical scenarios:
Use the Query field to apply advanced filtering with custom logic expressions
Combine multiple filter criteria to create highly specific activity subsets
When using Date grouping, adjust Time Range parameters to match your reporting periods
Test different grouping methods to discover engagement insights in your data
Complex queries with many filters or large date ranges may take longer to process. Consider narrowing your scope if chart generation is slow.
Additional Functions
Chart Type Selection
The Activity Summary widget supports ten different chart types to visualize your data effectively:
Bar: Vertical bars comparing activity volumes across categories (ideal for project or personnel comparisons)
Stacked Bar: Vertical bars with stacked segments showing composition within categories
Line: Connected points showing activity trends over time or across ordered categories
Monotone Line: Smoothed line chart for trend visualization without sharp angles
Area: Filled area chart emphasizing volume and magnitude of activity
Monotone Area: Smoothed area chart for cleaner trend visualization
Stacked Area: Multiple area series stacked to show cumulative totals and composition
Percent Area: Stacked area normalized to 100% to compare relative proportions
Pie: Circular chart showing proportional distribution (best for single-level categorical data)
Radar: Multi-axis chart comparing multiple variables simultaneously
After building your chart, locate the chart type selector in the widget interface
Click on different chart type options to switch visualization styles
Choose the chart type that best communicates your activity insights
Bar and line charts work best for time-based activity analyses, while pie charts are ideal for showing distribution across a limited number of personnel or projects.
Data Export
Export the underlying data used to generate your chart for further analysis or reporting:
After building your chart, locate the DOWNLOAD button in the widget interface
Click DOWNLOAD to export the aggregated activity data
Save the downloaded file to your desired location
The exported data includes all aggregated activity counts displayed in the chart, making it easy to:
Import into external analysis tools (Excel, R, Python)
Create custom reports and presentations
Archive analytical results for compliance documentation
Share usage insights with stakeholders who need raw data
Rebuilding Charts
Update your visualization when new activities occur or when you need different analytical perspectives:
Modify any query or chart configuration parameters as needed
Click BUILD CHART again to regenerate the visualization with updated settings
The widget will refresh to display your new chart configuration
Rebuild your charts regularly to monitor ongoing laboratory activity and track changes in system usage patterns over time.
Best Practices
Data Organization
Consistent Naming: Use standardized project and table names to ensure accurate grouping and meaningful chart labels
Date Range Focus: Start with narrow date ranges when exploring activity data, then expand to broader time periods for trend analysis
Strategic Filtering: Apply personnel or project filters to focus on specific research groups or initiatives
Logical Grouping: Choose grouping methods that align with your analytical goals (temporal trends use Date grouping, engagement tracking uses Personnel)
Performance Optimization
Limit Scope: When working with large activity datasets, use date range filters to improve chart generation speed
Selective Filtering: Apply table or project filters to reduce the volume of activity data being processed
Appropriate Time Units: Use larger time units (months or years) for long-term trend analysis to avoid excessive data points
Regular Monitoring: Build charts periodically rather than continuously to avoid system load
Analytical Strategy
Start Simple: Begin with activity count and basic grouping to understand overall usage patterns
Progressive Refinement: Add filters incrementally to drill down into specific areas of interest
Multiple Views: Create multiple widget instances with different configurations to compare different analytical perspectives
Chart Type Selection: Experiment with different chart types to find the most effective visualization for your activity patterns
Save commonly used configurations by documenting your query and chart settings, making it easy to recreate frequently needed activity reports.
Common Pitfalls to Avoid
Avoid: Using Date grouping without specifying appropriate time units for your analysis period
Instead: Match time units to your data span (days for weeks of data, months for years of data)
Avoid: Creating pie charts with too many personnel or project categories, which leads to cluttered and unreadable visualizations
Instead: Limit pie charts to 5–8 major categories for clear presentation
Avoid: Forgetting to rebuild charts after modifying configuration settings
Instead: Always click BUILD CHART after making any configuration changes
Reporting and Analytics
Regular Reviews: Schedule periodic chart generation to monitor ongoing laboratory engagement and usage trends
Comparative Analysis: Create multiple charts with different grouping methods to gain comprehensive insights into team behavior
Stakeholder Communication: Export data and share visualizations in team meetings and progress reports
Historical Tracking: Use consistent date ranges for period-over-period comparisons (e.g., monthly activity summaries)
Compliance and Documentation
Audit Support: Export and archive activity chart data regularly to supplement detailed audit trail records
Standardized Reporting: Establish standard configurations for recurring compliance and usage reports
Data Verification: Cross-reference chart results with audit trail views to verify accuracy of aggregated activity data
Access Control: Ensure appropriate personnel filters match your organization's data access policies
Related Widgets
Record Summary: Similar visualization widget that counts records instead of activities — use Record Summary to track data creation output and Activity Summary to track user engagement and system usage
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