Crowdsourced Visualization Ranking for Unstructured Data
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Solution Overview
Problem
Existing methods for sharing and evaluating crowd-sourced graphical representations of unstructured data are limited by the inability to facilitate collaboration and the need for human experts to manually rank and visualize data, making it difficult to discover high-value information within large volumes of unstructured data.
Innovation Solution
A system that uses one or more computer processors to display and rank user-generated data visualizations, allowing users to evaluate and modify charts, thereby crowdsourcing the process of effectively representing unstructured data, which reduces the need for individual users to generate charts from scratch.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human experts manually rank and evaluate data visualizations, then the quality of data representation is improved, but the time and labor required increases significantly
Solution Approach 1:
The system enables users to self-evaluate and self-rank data visualizations through an automated interface where users can view, compare, and rank multiple visualization options without requiring expert intervention. The system processes user rankings automatically to determine the best visualizations, freeing users from manual evaluation tasks while maintaining quality standards.
Solution Approach 2:
The system implements a feedback mechanism where users can rank multiple data visualization options and receive automated processing of their preferences. This feedback loop allows the system to learn from user preferences and improve future recommendations, reducing the need for repeated manual evaluations while maintaining high quality standards.
2Reliability
If competitors cannot see each other's entries during competition, then originality of data visualization is improved, but collaboration and learning from others is prevented
Solution Approach 1:
The system segments the data visualization process into independent evaluation phases where users can view and rank visualizations without seeing competitors' entries in real-time. This segmentation maintains originality by preventing direct influence between creators while allowing post-completion collaboration and learning through the ranking interface.
Solution Approach 2:
The system performs preliminary evaluation where users can view and rank data visualizations before final selection. This preliminary action allows users to compare options and learn from each other's work in advance, fostering collaboration and improvement without compromising the originality created during the independent visualization generation phase.
3Manufacturing precision
If individual users generate charts from scratch, then customization and quality control is improved, but the burden and time required increases
Solution Approach 1:
The system merges multiple data visualization options into a unified ranking interface where users can view and evaluate multiple charts simultaneously. This combining approach allows users to maintain quality control through careful selection while reducing the burden of creating each visualization from scratch by leveraging pre-generated options from multiple sources.
Solution Approach 2:
The system provides a universal interface that handles multiple functions: viewing various data visualization types, comparing options, ranking preferences, and learning from user feedback. This multi-functional approach increases productivity by consolidating multiple tasks into a single interface while maintaining quality control through user-driven evaluation.
Data Source
AI summary
According to embodiments of the present invention, one or more computer processors display unstructured data. One or more computer processors display a first chart that graphically represents at least a portion of the unstructured data. In response to the first chart failing to satisfy a user-defined criteria, one or more computer processors modifies the first chart to generate a second chart that graphically represents at least a portion of the unstructured data in a user-defined manner. In certain embodiments, the unstructured data includes information that does not have a pre-defined data model and/or is not organized in a pre-defined manner.