Interactive Tag Cloud for Big Data Visualization and Filtering
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Solution Overview
Problem
Large volumes of complex data in databases are difficult for non-developer users to visualize and understand due to their size and complexity, making it challenging to access and filter effectively.
Innovation Solution
An interactive tag cloud interface that visualizes and filters data by ranking relevant information based on criteria such as frequency of incidence or temporal information, allowing users to quickly assess data contours and focus on specific tasks without needing to drill down into details.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large volumes of complex data are stored in databases, then data capacity and information volume increase, but data transparency and understandability decrease for non-developer users
Solution Approach 1:
The patent segments large volumes of complex data into organized categories and dimensions, presenting them as structured groups rather than overwhelming raw data. This allows non-developer users to navigate and understand data by breaking it into manageable segments with clear labels and hierarchies.
Solution Approach 2:
The patent introduces an intermediary layer between the raw database and the user - a sophisticated data access interface that translates complex data structures into user-friendly presentations. This intermediary handles the complexity internally while presenting simplified views to users, resolving the contradiction between data volume and understandability.
2Loss of information
If the full scope of large data volumes is presented to users, then complete information is provided, but user comprehension and quick assessment become difficult
Solution Approach 1:
The patent implements a dynamic data presentation interface that adapts to user needs. It provides comprehensive data information while dynamically adjusting the level of detail, aggregation, and organization based on user interactions, allowing users to comprehend data at their preferred depth without losing information completeness.
Solution Approach 2:
The patent adds organizational dimensions to data presentation, such as hierarchical categories, temporal dimensions, and contextual groupings. This transforms flat, overwhelming data into multi-dimensional structures that users can navigate intuitively, maintaining information completeness while enhancing comprehension through additional organizational layers.
3Adaptability or versatility
If non-developer users access detailed data directly, then complete data access is achieved, but the complexity of data structures prevents effective utilization
Solution Approach 1:
The patent extracts and separates the complexity of data structures from the user interface. It pulls out the complex internal organization of database data and handles it internally through sophisticated processing, while presenting simplified, user-friendly data views that maintain full access capability without exposing structural complexity to non-developer users.
Solution Approach 2:
The patent changes the parameters of data presentation by transforming complex data structures into simplified representations. It adjusts parameters such as data aggregation levels, categorization schemes, and display formats to match user capabilities while preserving full data access, effectively resolving the contradiction between accessibility and structural complexity.
Data Source
AI summary
An interactive tag cloud provides an intuitive interface to large data volumes. Where the data is a large table, an overview afforded by the tag cloud may contain relevant table information ranked by priority and volume, represented in different categories. The tag cloud may be used to filter that big data in an efficient manner. This allows an ordinary (i.e., non-developer) user of the database to quickly assess high level contours of the data volumes, and also to filter that data in order to focus on specific tasks. The interactive tag cloud visualization may indicate data priority according to frequency of incidence of a dimension in database records, or according to other criteria such as importance derived from date information. The tag cloud affords visibility to aggregated big data content and also of filtered data, prior to the user having to immediately drill down in order to access details thereof.