Visualization Suggestion System Using Transition Rules
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional data analysis tools often leave users uncertain about the best next steps during data exploration, leading to a less powerful analysis experience and increased frustration due to the lack of intuitive guidance.
Innovation Solution
A system that provides visualization suggestions by generating and ranking possible next exploration steps based on contextually relevant and statistically interesting visualizations, such as charts, using transition rules and scoring algorithms to assist users in navigating data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional data analysis tools are used without guidance, then users have freedom to explore data, but users feel lost and frustrated due to lack of intuitive next steps
Solution Approach 1:
The system provides feedback to users by analyzing their current visualization and automatically generating suggested next steps. The system monitors user interactions and data exploration patterns, then returns relevant recommendations for subsequent visualizations, helping users navigate the data exploration process without feeling lost.
Solution Approach 2:
The system enables self-service by automatically generating visualization suggestions based on the current state of data exploration. Instead of requiring users to manually determine next steps, the system autonomously analyzes the data context and produces relevant visualization recommendations, reducing user cognitive load and frustration.
2Productivity
If users manually determine next exploration steps, then users have control over analysis direction, but analysis time increases due to lack of intuitive guidance
Solution Approach 1:
The system performs preliminary action by pre-calculating and generating suggested next visualization steps before users need to make decisions. By analyzing the current data state in advance and preparing relevant exploration paths, the system reduces the time users would otherwise spend manually determining next steps, thereby improving analysis efficiency.
Solution Approach 2:
The system provides timely feedback with visualization suggestions that appear contextually relevant to the current exploration state. This feedback mechanism helps users quickly identify productive next steps without wasting time on unproductive explorations, thus improving overall analysis productivity.
3Adaptability or versatility
If the system generates multiple visualization candidates, then visualization suggestions become more comprehensive, but system complexity increases
Solution Approach 1:
The system applies segmentation by dividing the complex task of generating visualization suggestions into distinct modules: data analysis module, visualization generation module, scoring module, and ranking module. Each segment handles a specific aspect of the complexity, making the overall system more manageable while maintaining comprehensive suggestion generation capabilities.
Solution Approach 2:
The system manages complexity by dynamically adjusting parameters such as the number of visualization candidates generated, the depth of data exploration, and the complexity of scoring criteria based on user needs and data characteristics. This allows the system to provide comprehensive suggestions when needed while reducing complexity for simpler scenarios.
Data Source
AI summary
Techniques of providing visualization suggestions are disclosed. In some example embodiments, a current visualization of at least a portion of data of a dataset is determined to be displayed to a user in a graphical user interface of a device, a plurality of visualization candidates is generated based on an application of transition rules to the current visualization, a corresponding score for each one of the plurality of visualization candidates is generated based on a corresponding level of data variance for the data of the corresponding visualization candidate, a ranking of the plurality of visualization candidates is generated based on the scores, at least one of the plurality of visualization candidates is selected based on the ranking, and a plurality of selectable visualization suggestions corresponding to the selected visualization candidates is caused to be displayed to the user in the graphical user interface of the device.