TripleGraph

Software · Tue Apr 07 00:00:00 EDT 2020

DOI:https://doi.org/10.11578/dc.20201001.87· OSTI ID:1631430 · Code ID:45844

Sangkeun, Matt Lee ^[1]

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1. Oak Ridge National Laboratory

RDF triplestores are great tools for online graph analytic processing (i.e., graph pattern query processing), but they do not provide graph mining capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.). The software title “TripleGraph” is a graph analysis toolkit, which uses an RDF triplestore as its backend for creating, manipulating, mining, and programming with large scale property graphs. It allows users to run various graph mining algorithms easily. User can import edgelist-formatted (homogeneous graph) or JSON-formatted graph (property graph) into the RDF triplestore using the provided tool and perform various analysis such as (1) Node/edge retrieval and manipulation, (2) Pathfinding between two given nodes, (3) Running graph mining algorithms (PageRank/Personalized PageRank, Single Source Shortest Path/Multi-Source Shortest Path, Connected Component, Node Eccentricity, Peer Pressure Clustering). It supports standard graph data format and works with a standard SPARQL endpoint like Jena Fuseki. It allows users to perform online graph analytic processing and graph mining on the same platform (a triplestore).

• Short Name / Acronym: TripleGraph
• Project Type: Open Source, Publicly Available Repository
• Site Accession Number: 8144
• Software Type: Scientific
• License(s): MIT License
• Programming Language(s): Python 2.7
• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE

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  Primary Award/Contract Number:

  AC05-00OR22725
• DOE Contract Number: AC05-00OR22725
• Code ID: 45844
• OSTI ID: 1631430
• Country of Origin: United States