Tabular Graph Editor for High-Cardinality Data
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Solution Overview
Problem
Current systems face challenges in effectively browsing and editing higher-arity and higher-cardinality relationships in graph-structured data, particularly in visualizing and manipulating nodes with multiple attributes, and in managing redundancy and ambiguity when using tables to represent these relationships.
Innovation Solution
A tabular graph editor system that employs a workflow involving OLAP roll-up, Least Common Subsumer algorithms, and property paths to simplify navigation, reduce redundancy, and manage attribute inheritance, allowing users to configure views and filters to efficiently browse and edit graph data in a table format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Shape
If graph data is visualized using nodes and edges, then the graph structure can be displayed, but it becomes impractical to compare attributes of nodes across multiple dimensions
Solution Approach 1:
The patent transforms graph data from a two-dimensional node-edge visualization into a multi-dimensional tabular structure with page headers, row headers, and column headers. This dimensional transformation enables efficient attribute comparison across multiple dimensions while preserving the underlying graph relationships through hierarchical organization and drill-down capabilities.
2Ease of operation
If tables are used to represent graph relationships, then attribute comparison becomes efficient, but redundancy and ambiguity increase when representing higher-arity and higher-cardinality relationships
Solution Approach 1:
The patent segments the table structure into distinct hierarchical levels: page headers for higher-arity relationships, row headers for subject nodes, and column headers for predicates and objects. This segmentation allows each part of the table to serve a specific function, reducing redundancy by clearly defining the role of each cell while maintaining efficient attribute comparison capabilities.
Solution Approach 2:
The patent introduces additional dimensional layers to the table structure through hierarchical headers and drill-down capabilities. Page headers represent one dimension of relationships, row headers represent another dimension, and column headers represent a third dimension. This multi-dimensional organization resolves ambiguity by providing clear contextual information at each level while reducing redundancy through hierarchical inheritance.
3Adaptability or versatility
If junction tables are created for many-to-many joins in SQL, then relational data can be queried, but the queries become complex to write and slow to execute
Solution Approach 1:
The patent extracts the complex join operations from traditional SQL queries by directly representing many-to-many relationships in the graph structure. Instead of requiring junction tables and recursive queries, the system allows direct traversal of graph edges to compile groups of related nodes, significantly simplifying the query process and improving execution speed while maintaining full relational querying capabilities.
Data Source
AI summary
A system and method that implements a tabular graph editor are disclosed. The system supports employing tables to browse and edit comparisons by multiple attributes of nodes in a graph.