Nested Data Mark Sorting in Visualization Panes
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Solution Overview
Problem
Current data visualization tools fail to sort data marks at differing levels of granularity, leading to unintuitive user interactions and mismatched sorting expectations, as they do not allow independent sorting within groups in data visualizations.
Innovation Solution
Implementing a nested sort operation that allows data marks within different panes of a data visualization to be independently ordered, enabling users to sort at varying levels of granularity by partitioning data into groups and subgroups based on user-defined field associations and aggregations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current sorting approaches are used, then data marks are sorted globally across the entire visualization, but data marks at differing levels of granularity cannot be sorted independently
Solution Approach 1:
The patent segments the data visualization into multiple panes or groups based on hierarchical categories, allowing independent sorting within each segment. This enables users to sort data marks at different levels of granularity without affecting other groups, directly resolving the contradiction between sorting flexibility and operational intuitiveness.
Solution Approach 2:
The patent implements nested sorting where data marks are sorted within groups, which are themselves sorted within larger categories, creating a hierarchical sorting structure. This nested approach allows users to apply sorting operations at multiple levels simultaneously, providing both global and local sorting control while maintaining intuitive user interaction.
2Adaptability or versatility
If nested sort operation is implemented, then data marks within different panes can be independently ordered, but device complexity increases
Solution Approach 1:
By segmenting the sorting operation into independent pane-level sorts rather than a single global sort, the system achieves nested sorting capability without requiring complex cross-pane coordination logic. Each pane maintains its own sort state independently, simplifying the overall system architecture while providing advanced sorting functionality.
Solution Approach 2:
Each pane or group of data marks performs self-service sorting independently, managing its own sort order without requiring centralized control from other panes. This self-service approach reduces system complexity by eliminating the need for complex inter-pane coordination while still providing comprehensive nested sorting capability across the entire visualization.
Data Source
AI summary
A data visualization application receives user actions to (i) associate a first data field with a first shelf and (ii) associate second and third data fields with a second shelf. The method receives an additional user action to specify a nested sort according to data for the first and third data fields. The method generates and displays a data visualization in accordance with the received actions, including: (i) partitioning retrieved data into groups of tuples, each tuple including data for the data fields, and each group of tuples corresponding to a distinct value of the second data field, (ii) forming panes, each pane corresponding to a respective group of tuples, and (iii) within each pane, displaying data marks, each data mark corresponding to a respective tuple.