Systems and Methods for 3D Data Visualization and Network Extraction

A data visualization method comprising:

• obtaining a graph comprising a plurality of nodes and a plurality of edges;
• identifying a plurality of communities in the graph, where each community comprises nodes from the plurality of nodes;
• generating a community graph structure based on the identified communities;
• where the community graph comprises a plurality of supernodes and a plurality of superedges;
• where each supernode in the plurality of supernodes represents nodes in the plurality of nodes being part of the same community;
• and
• where each superedge in the plurality of superedges connects two supernodes, and represents edges in the plurality of edges connecting nodes represented by the two supernodes;
• spatializing the community graph structure;
• unpacking the spatialized community graph structure into an unpacked graph structure comprising the plurality of nodes and the plurality of edges, where each node in the plurality of nodes is located at approximately the position of the supernode that represented it;
• spatializing the unpacked graph structure;
• and
• providing the spatialized unpacked graph structure.

The data visualization system of method 18, wherein converting the tabular data structure into a graph structure comprises:

• identifying a node column from the plurality of columns;
• identifying a plurality of associative columns from the plurality of columns;
• generating a set of nodes based on values in the node column, where each node in the set of nodes represents a value in the node column without duplication;
• constructing a reverse index of the tabular data structure, where:
• the reverse index comprises a set of key-value pairs;
• a key in a given key-value pair is a given value from the plurality of associative columns without duplication;
• and
• a value in the given key-value pair is a list of values from the node column that appear on the same row as the given value from the plurality of associative columns without duplication;
• constructing a set of edges based on the reverse index, where each edge in the set of edges is constructed by connecting every combination of node values in the value of each key-value pair;
• constructing an edgelist from the set of edges, where the edgelist comprises a list of every edge in the set of edges;
• replacing edges in the edgelist having identical endpoints with a single edge, where a weight of the replacement edge is equal to the sum of edge weights of the replaced edges;
• and
• constructing a graph structure using edges in the edgelist to connect nodes in the set of nodes.