graph query language for analyzing data graphs david silberberg, paul frank, wayne bethea and john...
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Graph Query Language for Analyzing Data Graphs
David Silberberg, Paul Frank, Wayne Bethea and John Gersh – Inventors
Goals and Approach
• Goals– Increase the velocity of analysis through a comprehensive graph
query language for information discovery– Reduce by orders of magnitude the time to perform analysis on
data represented as a graph
• Approach– Create a declarative graph query language that integrates and
unifies multiple analysis approaches• Pattern matching• Traditional graph discovery algorithms (e.g., shortest path, minimal
spanning tree, etc.)• Social network algorithms (e.g., centrality, betweenness, etc.)• Special analysis features• Ontology-assisted graph query
– Can be overlaid on top of existing relational databases
Concept of Operations
Graph Query
Example Scenario• Farmer Jones' lettuce crop did well this year, but few other farmers did well.
Why?• First, find Farmer Jones. (Browsing)
Jones
Example Scenario• Rabbits usually eat lettuce. Let's find the rabbits that ate Farmer Jones' lettuce.
(Pattern Search)
Jones
Prize
Roman
Icy
Bugs
Harvey
Example Scenario• Let's look at all the farmers, and their locations, whose lettuce was eaten by fewer
than 5 rabbits. (Pattern Search)
Jones
Smith
Harris
Prize
Roman
Icy
Leafy
Soft
Crispy Green
Tasty
Bugs
Harvey
Peter
Smalltown,USA
Example Scenario• What commonalities do the farmers have with each other and with the rabbits?
(Pattern Search and Algorithmic Search [e.g., ShortestPath])
Jones
Smith
Harris
Prize
Roman
Icy
Leafy
Soft
CrispyGreen
Tasty
Bugs
Harvey
Peter
Smalltown,USA
Red
Sly
Acme Rent-a-Fox
Example Scenario• If Fred rabbit ate Prize lettuce, what else would we learn? (Analysis-Specific Search
[e.g., Hypothesis], Pattern Search, and Algorithmic Search [e.g. Shortest Path])
Jones
Smith
Harris
Prize
Roman
Icy
Leafy
Soft
CrispyGreen
Tasty
Bugs
Harvey
Peter
Smalltown,USARed
Sly
Acme Rent-a-Fox
Fred
Brer
Fox Enterprises
Technology Applications
• Enhance traditional database engines
• Augment search engine technology
• Social networking websites
• Tools for analysis of complex relationships
• Support complex visualization tools
Commercial Applications
• Telecommunications
• Competition analysis
• Financial analysis
• Semantic web search
• Social network analysis
• Biology & Bioinformatics research
Commercial Opportunities
• Technology is available for licensing in all fields of use
• Potential standardization of this technology– ANSI INCITS– ISO/IEC
Contact Information
• For technical information contact:
David Silberberg, [email protected]
• For licensing information contact:
Susan Furney, Technology AssociateOffice of Technology TransferThe Johns Hopkins UniversityApplied Physics Laboratory11100 Johns Hopkins RoadLaurel, MD [email protected]/ott