A Graph is a pictorial aid for representing Entity Relationship Types. It comprises a collection of nodes and connectors representing an Entity, an Attribute, and a Value.

What is the difference between a Graph and a Network?

Graphs are generic depictions of Entity Relationship Types, while Networks are specific Graphs that depict relations that are, at the very least, transitive in nature.

Why are Graph Analytics important?

Graph Analytics are important because Entity Relationships model the real world and provide a powerful basis for knowledge acquisition and dissemination, leveraging computer software for productivity.

What is Centrality in a graph?

Centrality measures the importance of a node in a graph simply by how 'central' the node is, relative to others in the same graph.

What is Degree Centrality?

Degree Centrality measures network importance based on the number of in-bound connections from other nodes or out-bound connections to other nodes, given a starting node.

What is Closeness Centrality?

Closeness Centrality is based on the number of 'hops' between two nodes, calculated using the shortest path between each pair of nodes.

What is Betweenness Centrality?

Betweenness Centrality assigns importance to a node based upon the number of times that node occurs within the shortest paths between all pairs of nodes in a graph.

What is Eigen Vector Centrality (EVC)?

The Eigen Vector Centrality (EVC) metric measures the importance of a node in a graph based on the importance of its neighbors, identifying key influencers.

How can you combine SQL and SPARQL for Graph Analytics?

Virtuoso's SQL engine includes a Transitivity extension that is surfaced in its SPARQL engine as SPARQL-BI, allowing both query languages to be used together for graph analytics.

Graph Analytics using Virtuoso’s SPARQL-BI extensions to SPARQL

The Challenge & The Solution 🔗

The Data Silo Problem

Traditional data systems struggle to represent and query complex relationships. Valuable insights remain hidden in disconnected datasets, making it difficult to understand the true value and influence of entities within a network.

The Virtuoso Solution

Virtuoso's SPARQL-BI extensions merge the power of SQL and SPARQL. By leveraging a Transitivity engine, it allows for sophisticated graph analytics directly within the database, turning relationship data into a competitive advantage.

Core Concepts in Graph Analytics 🔗

Graph

A pictorial representation of Entity Relationship Types, comprising a collection of nodes and connectors that represent an Entity, its Attribute, and its Value.

Network

A sub-category of a Graph that depicts Entity Relationship Types that are transitive in nature, meaning all nodes in the graph represent relatives by varying degrees.

Social Network

A network constructed from connections like 'knows', 'friend', or 'follows' that denote transitive entity relationship types.

Friend Network

A network where each connection denotes a transitive relationship type that is also symmetric in nature, indicated by bidirectional arrows.

Implementation Strategy 🔗

1

Describe the Social Network

Create an RDF document comprising sentences that describe the social network’s membership, for instance, using RDF-Turtle notation and the FOAF vocabulary.

2

Load the RDF Document

Load the RDF document to a Virtuoso instance. For example, you can sponge (import) the document using our URIBurner service.

3

Write SPARQL-BI Queries

Write your queries using SPARQL-BI, leveraging Virtuoso's transitivity extensions to perform graph analytics operations like centrality calculations.

4

Execute Queries

Execute your SPARQL-BI queries against the loaded data in your Virtuoso instance to extract insights from the graph.

5

Share Results

Share your Query Results pages with others via your internal network or the World Wide Web to disseminate the knowledge.

Live Graph Analytics Queries 🔗

Frequently Asked Questions 🔗

Unleash Your Data's Potential 🔗

Contrary to general misconceptions, the open standards of SQL and SPARQL can be powerfully combined for Graph Analytics. Virtuoso provides the engine to not only make this possible but to do so with performance and scale, preserving your ability to mix and match best-of-class products.

Learn More About Virtuoso

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Graph Analytics with SPARQL-BI