Galaxy: A Platform for Explorative Analysis of Open Data Graphs

Galaxy is a platform designed for the explorative analysis of interconnected Open Data sources, such as social and information systems. It was developed by Seyed-Mehdi-Reza Beheshti at UNSW Sydney. The platform facilitates analysis of complex, semi-structured networks using abstractions like folders and paths, and leverages Hadoop for storing and processing large volumes of RDF triples.

Use Cases

• Perform exploratory relationship discovery among entities based on the graph structure of Linked Open Data.
• Group related entities within a semantic graph for analysis based on the described folder abstraction.
• Find and analyze paths between entities in a large-scale RDF graph using the described path abstraction.

Strengths

• Platform is built on W3C standards for Linked Open Data, suggesting interoperability.
• Designed to handle web-scale processing of Semantic Web data using Hadoop.
• Extends SPARQL with Folder-Path abstractions to enable more explorative analysis.

Limitations

• Row count, file formats, and data size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

UNSW Sydney

Collection Method

Platform for analyzing aggregated Open Data sources.