Interactive Cross-Analysis of Tabular Datasets via Segmented Data Access
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Solution Overview
Problem
Current data sharing methods, such as file downloading and API access, face challenges including loss of data ownership, difficulty in cross-analyzing multiple datasets, and inefficient access control, making it hard to derive useful insights from distributed data.
Innovation Solution
A data exploration apparatus and method that allows interactive cross-analysis of multiple tabular datasets without sharing raw data, by using a processor to launch explorations, apply filters, and display working scenes, enabling users to perform operations and switch between datasets while protecting data from unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data is shared through file downloading or API access, then data accessibility is improved, but data ownership is lost and security is compromised
Solution Approach 1:
The patent segments data access into multiple hierarchical levels: raw data storage, processed data generation, and result visualization. Each level is controlled independently, allowing users to access only the necessary portion of data while the data owner retains control over the raw data and its processing logic.
Solution Approach 2:
The patent introduces an intermediary processing system that sits between the data owner and the user. This intermediary executes processing logic locally, generates results, and transmits only the processed outcomes to users, preventing direct access to raw data while still enabling data utilization.
2Adaptability or versatility
If multiple datasets are collected for cross-analysis, then analysis capability is improved, but data preparation complexity and time consumption increase
Solution Approach 1:
The patent implements preliminary action by pre-processing datasets and establishing data relationships in advance. The system automatically identifies and links related data fields across different datasets before analysis is requested, eliminating the need for users to manually prepare and align multiple datasets at the time of analysis.
3Ease of operation
If complete datasets are downloaded for local storage, then data availability is improved, but storage requirements and loading time increase
Solution Approach 1:
The patent extracts only the essential processed results and relevant data subsets needed for analysis, rather than requiring complete dataset downloads. The system transmits minimal necessary data after processing, significantly reducing storage requirements while maintaining data availability for the intended analysis purpose.
Data Source
AI summary
A data exploration apparatus is interactively operated by a user conducting a mission including explorations, T1, T2, . . . , TN, to cross-analyze tabular datasets, D1, D2, . . . , DN, respectively. The apparatus starts with n=1 in response to the initiation of the mission to launch an exploration Tn, enable the display device to display a working scene Sn for the exploration Tn, perform a sequence of operations on the working dataset Wn corresponding to the exploration Tn, and then refresh the working scene Sn. In response a GUI action, an interrupt operation is performed to escape from the exploration Tn, launch an exploration Tm with the target of interest TOI(n,m) to explore the related tabular dataset Dm, and enable the display device to display a working scene Sm for the exploration Tm.