Data Metric Objects for Visual Data Mark Selection
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Solution Overview
Problem
Complex data visualization systems with large or multiple data fields can be difficult for users to navigate and analyze effectively, as key functionalities may be hard to find or use within the user interface.
Innovation Solution
The system allows users to create summary metrics through user interaction with data marks of existing data visualizations by selecting a subset of visual data marks, generating a metric window with configuration options, and scheduling recurring data updates, enabling the creation of data metric objects that provide quick updates and summaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users interact with complex data visualization systems containing large or multiple data fields, then comprehensive data analysis capability is improved, but user interface complexity and difficulty of operation increase
Solution Approach 1:
The patent segments the complex data analysis task into distinct interactive components: (1) selecting individual data marks from visualizations, (2) creating metric objects from selected marks, (3) configuring metric properties through separate controls, and (4) organizing metrics in a hierarchical structure. This segmentation allows users to interact with manageable units rather than overwhelming complexity, resolving the contradiction between comprehensive analysis capability and ease of operation.
Solution Approach 2:
The patent introduces metric objects as intermediary elements between raw data visualizations and user analysis needs. These metric objects serve as mediators that encapsulate complex data processing logic while presenting simplified interaction interfaces. Users interact with metric objects rather than directly with underlying data fields, reducing interface complexity while maintaining analytical power.
2Loss of information
If the system provides comprehensive data visualization and analysis tools, then data understanding capability is improved, but system complexity increases
Solution Approach 1:
The patent creates metric objects that are simplified copies or representations of complex data visualizations. Each metric object captures essential data characteristics and relationships from the source visualization while presenting a streamlined interface. This copying approach allows the system to maintain comprehensive data understanding capabilities while reducing the apparent complexity users must manage.
Solution Approach 2:
The system performs preliminary data processing and metric configuration actions automatically when users create metric objects. Configuration parameters, data extraction logic, and update schedules are pre-established through the metric object creation process, reducing the complexity of subsequent data analysis operations while maintaining comprehensive understanding capabilities.
3Productivity
If users can create custom metrics from data marks, then data summarization capability is improved, but user interaction complexity increases
Solution Approach 1:
The patent enables users to create metric objects through direct interaction with data marks in visualizations. The system automatically derives configuration parameters from the selected data marks and their visual properties, allowing users to create summarized metrics through intuitive selection rather than complex configuration. This self-service approach improves data summarization productivity while minimizing interaction complexity by leveraging the visualization context.
Data Source
AI summary
A method visualizes data sources. A user selects a data source, and the computer system displays a first data visualization according to placement of data fields in shelves of the user interface. The data visualization comprises visual data marks representing the data source. A user selects some of the data marks. In response, the system displays a metric window including a data metric object preview, a summary of the selected data marks, and setting controls. The user provides input to create the data metric object. In response, the system creates the data metric object, including: configuration parameters derived from the first data visualization; an initial extract from the data source according to the configuration parameters; and a schedule for recurring retrieval of data from the data source to update the extract. The system then displays a second data visualization according to the configuration parameters and the extract.