Dynamic Interactive Data Visualization via Self-Service Query Generation
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Solution Overview
Problem
Current data visualization technologies are rigid and fixed, limiting user interactions to only drill down, trace up, and combine, and do not support dynamic queries outside the original data context, making users reliant on programmers for customization.
Innovation Solution
A method that dynamically determines pre-set and user-specified values for categorical and numerical vocabularies, allowing for flexible interactive data visualization by generating sub-queries and combining result sets, enabling users to define value segments and perform queries on new data sources without programming requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If programmers have total control of data visualization interactions, then the system maintains stability and predictability, but user flexibility and adaptability are severely restricted
Solution Approach 1:
The system enables users to perform data exploration operations independently without programmer intervention. Users can dynamically add data sources, define value segments, and execute queries through a self-service interface that automatically generates and processes queries, eliminating the need for programmers to re-program visualizations for each user need
Solution Approach 2:
The system segments the data exploration process into independent modular operations: adding data sources, defining value segments for categorical/numerical vocabularies, and executing queries. Each operation can be performed independently and combined flexibly, allowing users to build custom exploration workflows without requiring complete re-programming
2Adaptability or versatility
If data visualization interactions are fixed and preset, then the system maintains simplicity and ease of operation, but user autonomy and exploratory capability are limited
Solution Approach 1:
The system transitions from static preset interactions to dynamic user-driven interactions. Users can dynamically add new data sources at runtime, define custom value segments for vocabularies, and execute queries that adapt to their specific exploration needs, making the system as flexible as it is simple to use
Solution Approach 2:
The system introduces an intermediary layer between the user and the data source that handles query generation and processing automatically. This intermediary manages the complexity of dynamic query construction, allowing users to perform complex operations through simple interface interactions without directly dealing with query syntax or data processing complexity
3Adaptability or versatility
If users require programming capabilities to customize data visualization, then system functionality is comprehensive, but user accessibility and ease of use are reduced
Solution Approach 1:
The system replaces the mechanical requirement of programming with an automated query generation mechanism. Instead of users writing code to customize visualizations, the system automatically generates and processes queries based on user selections through the interface, substituting manual programming effort with automated processing
4Adaptability or versatility
If data visualization supports only original data context, then system reliability is maintained, but user exploratory freedom and analytical depth are constrained
Solution Approach 1:
The system provides universal data exploration capabilities that work across multiple data sources and contexts. Users can add different types of data sources (files, databases, APIs) and perform the same exploration operations on each, making the system equally effective whether working with original data or new external data sources
Data Source
AI summary
A method and system are provided for interactive data visualization. The method includes dynamically determining, responsive to a user request directed to at least one of default categories identified by analyzing a data source used with an initial user query, pre-set values for categorical portions and numerical portions of vocabularies for user selection using data analytics on the data source. The method also includes providing the user with a capability to specify other values for the portions. The method additionally includes dynamically generating multiple sub-queries to the data source for the pre-set values and at least one of the other values specified by the user for the portions. The method further includes generating a data visualization of combined result sets for the multiple sub-queries and displaying the data visualization.