SlideShare a Scribd company logo
Challenges in Knowledge
Graph Visualization
by GraphAware, world’s #1 Neo4j consultancy
graphaware.com
@graph_aware
Speaker
Jan Zak
jan.zak@graphaware.com
Twitter: @zakjan
● Senior Consultant at GraphAware
● data visualizations, maps, graphs
● not just lots of nodes, but also lots of node types with
different levels of importance
● challenges of full visualization
○ rendering performance, layout quality
○ too many different colors hurts
overview comprehensibility
Knowledge Graph
● opposed to Search & Expand
● Ben Shneiderman: The Eyes Have It: A Task by Data
Type Taxonomy for Information Visualizations
○ Visual Information-Seeking Mantra: Overview first, zoom and filter, then
details-on-demand
overview detail
Overview & Detail-on-demand
● maps are graphs
○ real objects as nodes
○ neighbourhood connections as edges
● Overview & Detail-on-demand
○ configurable zoom level to display each object type
● yet, generic graphs are more complex
○ nodes position in visualization is not known before, must be computed by
layout algorithm
○ nodes can be connected to any other nodes
in the graph (possibly leading to supernodes)
Analogy – Vector maps
Demo
● allows to create and return a virtual edge between any
two nodes
CALL apoc.create.vRelationship(n, 'TO', {}, m)
APOC Virtual Edges
● all paths between a set of nodes
MATCH (n:Outer) WITH collect(n) AS nodes
CALL apoc.path.expandConfig(nodes, {
terminatorNodes: nodes, maxLevel: 10
}) YIELD path AS p
RETURN p
● before APOC Fall Release 3.5.0.5
○ terminatorNodes + filterStartNode=false (default) was filtering out the
terminator nodes
○ https://github.com/neo4j-contrib/neo4j-apoc-procedures/pull/1290
MATCH (n:Outer) WITH collect(n) AS nodes
UNWIND nodes AS n
WITH n, [m IN nodes WHERE n <> m] AS terminatorNodes
CALL apoc.path.expandConfig(n, {
terminatorNodes: terminatorNodes, maxLevel: 10
}) YIELD path AS p
RETURN p
APOC Path Expanders
1. Easy: Full render of huge graphs is not useful, because:
A. technological limitation, slow rendering and layout performance
B. comprehensibility limitation, too complex to extract insights from it
C. both
2. Medium: How many max colors is recommended for a
categorical measure?
A. less than 10
B. less than 20
C. no limit
3. Hard: What’s the change in APOC Fall Release 3.5.0.5 in
behavior of Path Expander?
A. filterStartNode=false doesn’t filter terminationNodes anymore
B. beginSequenceAtStart=false doesn’t filter terminationNodes anymore
C. both
Answer here: r.neo4j.com/hunger-games
Hunger Games Questions
for “Challenges in knowledge graph visualization”

More Related Content

What's hot

Graph Analytics: Graph Algorithms Inside Neo4j
Graph Analytics: Graph Algorithms Inside Neo4jGraph Analytics: Graph Algorithms Inside Neo4j
Graph Analytics: Graph Algorithms Inside Neo4jNeo4j
 
Functional APIs with Absinthe GraphQL
Functional APIs with Absinthe GraphQLFunctional APIs with Absinthe GraphQL
Functional APIs with Absinthe GraphQLZvi Avraham
 
Neo4j Spatial at LocationDay 2013 in Malmö
Neo4j Spatial at LocationDay 2013 in MalmöNeo4j Spatial at LocationDay 2013 in Malmö
Neo4j Spatial at LocationDay 2013 in MalmöCraig Taverner
 
IPTC News Exchange Working Group 2013 Autumn Meeting
IPTC News Exchange Working Group 2013 Autumn MeetingIPTC News Exchange Working Group 2013 Autumn Meeting
IPTC News Exchange Working Group 2013 Autumn MeetingStuart Myles
 
Kubernetes Config Management Landscape
Kubernetes Config Management LandscapeKubernetes Config Management Landscape
Kubernetes Config Management LandscapeTomasz Tarczyński
 
OrientDB - the 2nd generation of (Multi-Model) NoSQL - J On The Beach 2016
OrientDB - the 2nd generation of (Multi-Model) NoSQL  - J On The Beach 2016OrientDB - the 2nd generation of (Multi-Model) NoSQL  - J On The Beach 2016
OrientDB - the 2nd generation of (Multi-Model) NoSQL - J On The Beach 2016Luigi Dell'Aquila
 
Introduction to Fluvio Data Engineer.pdf
Introduction to Fluvio Data Engineer.pdfIntroduction to Fluvio Data Engineer.pdf
Introduction to Fluvio Data Engineer.pdfSehz1
 
Trondheim Eclipe Day 2015 and 2016
Trondheim Eclipe Day 2015 and 2016Trondheim Eclipe Day 2015 and 2016
Trondheim Eclipe Day 2015 and 2016Matthew Gerring
 
Practical Graph Algorithms with Neo4j
Practical Graph Algorithms with Neo4jPractical Graph Algorithms with Neo4j
Practical Graph Algorithms with Neo4jjexp
 
Full Stack Development with Neo4j and GraphQL
Full Stack Development with Neo4j and GraphQLFull Stack Development with Neo4j and GraphQL
Full Stack Development with Neo4j and GraphQLNeo4j
 
Building Community APIs using GraphQL, Neo4j, and Kotlin
Building Community APIs using GraphQL, Neo4j, and KotlinBuilding Community APIs using GraphQL, Neo4j, and Kotlin
Building Community APIs using GraphQL, Neo4j, and KotlinNeo4j
 
Introduction to QML
Introduction to QMLIntroduction to QML
Introduction to QMLAlan Uthoff
 
OrientDB - the 2nd generation of (Multi-Model) NoSQL
OrientDB - the 2nd generation  of  (Multi-Model) NoSQLOrientDB - the 2nd generation  of  (Multi-Model) NoSQL
OrientDB - the 2nd generation of (Multi-Model) NoSQLLuigi Dell'Aquila
 
Building a Knowledge Graph using NLP and Ontologies
Building a Knowledge Graph using NLP and OntologiesBuilding a Knowledge Graph using NLP and Ontologies
Building a Knowledge Graph using NLP and OntologiesNeo4j
 
OSMC 2018 | Stream connector: Easily sending events and/or metrics from the C...
OSMC 2018 | Stream connector: Easily sending events and/or metrics from the C...OSMC 2018 | Stream connector: Easily sending events and/or metrics from the C...
OSMC 2018 | Stream connector: Easily sending events and/or metrics from the C...NETWAYS
 
OSMC 2018 | Visualization of your distributed infrastructure by Nicolai Buchwitz
OSMC 2018 | Visualization of your distributed infrastructure by Nicolai BuchwitzOSMC 2018 | Visualization of your distributed infrastructure by Nicolai Buchwitz
OSMC 2018 | Visualization of your distributed infrastructure by Nicolai BuchwitzNETWAYS
 
No Sql in Enterprise Java Applications
No Sql in Enterprise Java ApplicationsNo Sql in Enterprise Java Applications
No Sql in Enterprise Java ApplicationsPatrick Baumgartner
 
Graphs & Neo4j - Past Present Future
Graphs & Neo4j - Past Present FutureGraphs & Neo4j - Past Present Future
Graphs & Neo4j - Past Present Futurejexp
 

What's hot (20)

Graph Analytics: Graph Algorithms Inside Neo4j
Graph Analytics: Graph Algorithms Inside Neo4jGraph Analytics: Graph Algorithms Inside Neo4j
Graph Analytics: Graph Algorithms Inside Neo4j
 
Functional APIs with Absinthe GraphQL
Functional APIs with Absinthe GraphQLFunctional APIs with Absinthe GraphQL
Functional APIs with Absinthe GraphQL
 
Neo4j Spatial at LocationDay 2013 in Malmö
Neo4j Spatial at LocationDay 2013 in MalmöNeo4j Spatial at LocationDay 2013 in Malmö
Neo4j Spatial at LocationDay 2013 in Malmö
 
IPTC News Exchange Working Group 2013 Autumn Meeting
IPTC News Exchange Working Group 2013 Autumn MeetingIPTC News Exchange Working Group 2013 Autumn Meeting
IPTC News Exchange Working Group 2013 Autumn Meeting
 
Kubernetes Config Management Landscape
Kubernetes Config Management LandscapeKubernetes Config Management Landscape
Kubernetes Config Management Landscape
 
OrientDB - the 2nd generation of (Multi-Model) NoSQL - J On The Beach 2016
OrientDB - the 2nd generation of (Multi-Model) NoSQL  - J On The Beach 2016OrientDB - the 2nd generation of (Multi-Model) NoSQL  - J On The Beach 2016
OrientDB - the 2nd generation of (Multi-Model) NoSQL - J On The Beach 2016
 
Introduction to Fluvio Data Engineer.pdf
Introduction to Fluvio Data Engineer.pdfIntroduction to Fluvio Data Engineer.pdf
Introduction to Fluvio Data Engineer.pdf
 
Trondheim Eclipe Day 2015 and 2016
Trondheim Eclipe Day 2015 and 2016Trondheim Eclipe Day 2015 and 2016
Trondheim Eclipe Day 2015 and 2016
 
Practical Graph Algorithms with Neo4j
Practical Graph Algorithms with Neo4jPractical Graph Algorithms with Neo4j
Practical Graph Algorithms with Neo4j
 
Full Stack Development with Neo4j and GraphQL
Full Stack Development with Neo4j and GraphQLFull Stack Development with Neo4j and GraphQL
Full Stack Development with Neo4j and GraphQL
 
Building Community APIs using GraphQL, Neo4j, and Kotlin
Building Community APIs using GraphQL, Neo4j, and KotlinBuilding Community APIs using GraphQL, Neo4j, and Kotlin
Building Community APIs using GraphQL, Neo4j, and Kotlin
 
Hadoop @ eBuddy
Hadoop @ eBuddyHadoop @ eBuddy
Hadoop @ eBuddy
 
Introduction to QML
Introduction to QMLIntroduction to QML
Introduction to QML
 
OrientDB - the 2nd generation of (Multi-Model) NoSQL
OrientDB - the 2nd generation  of  (Multi-Model) NoSQLOrientDB - the 2nd generation  of  (Multi-Model) NoSQL
OrientDB - the 2nd generation of (Multi-Model) NoSQL
 
Building a Knowledge Graph using NLP and Ontologies
Building a Knowledge Graph using NLP and OntologiesBuilding a Knowledge Graph using NLP and Ontologies
Building a Knowledge Graph using NLP and Ontologies
 
OSMC 2018 | Stream connector: Easily sending events and/or metrics from the C...
OSMC 2018 | Stream connector: Easily sending events and/or metrics from the C...OSMC 2018 | Stream connector: Easily sending events and/or metrics from the C...
OSMC 2018 | Stream connector: Easily sending events and/or metrics from the C...
 
OSMC 2018 | Visualization of your distributed infrastructure by Nicolai Buchwitz
OSMC 2018 | Visualization of your distributed infrastructure by Nicolai BuchwitzOSMC 2018 | Visualization of your distributed infrastructure by Nicolai Buchwitz
OSMC 2018 | Visualization of your distributed infrastructure by Nicolai Buchwitz
 
Linq
LinqLinq
Linq
 
No Sql in Enterprise Java Applications
No Sql in Enterprise Java ApplicationsNo Sql in Enterprise Java Applications
No Sql in Enterprise Java Applications
 
Graphs & Neo4j - Past Present Future
Graphs & Neo4j - Past Present FutureGraphs & Neo4j - Past Present Future
Graphs & Neo4j - Past Present Future
 

Similar to Challenges in knowledge graph visualization

Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...Databricks
 
Machine Learning and GraphX
Machine Learning and GraphXMachine Learning and GraphX
Machine Learning and GraphXAndy Petrella
 
SCALABLE PATTERN MATCHING OVER COMPRESSED GRAPHS VIA DE-DENSIFICATION
SCALABLE PATTERN MATCHING OVER COMPRESSED GRAPHS VIA DE-DENSIFICATIONSCALABLE PATTERN MATCHING OVER COMPRESSED GRAPHS VIA DE-DENSIFICATION
SCALABLE PATTERN MATCHING OVER COMPRESSED GRAPHS VIA DE-DENSIFICATIONaftab alam
 
Multiple graphs in openCypher
Multiple graphs in openCypherMultiple graphs in openCypher
Multiple graphs in openCypheropenCypher
 
Streaming Python on Hadoop
Streaming Python on HadoopStreaming Python on Hadoop
Streaming Python on HadoopVivian S. Zhang
 
Distributed graph processing
Distributed graph processingDistributed graph processing
Distributed graph processingBartosz Konieczny
 
Computer Graphics - Lecture 01 - 3D Programming I
Computer Graphics - Lecture 01 - 3D Programming IComputer Graphics - Lecture 01 - 3D Programming I
Computer Graphics - Lecture 01 - 3D Programming I💻 Anton Gerdelan
 
Benchmarking Tool for Graph Algorithms
Benchmarking Tool for Graph AlgorithmsBenchmarking Tool for Graph Algorithms
Benchmarking Tool for Graph AlgorithmsYash Khandelwal
 
Multiple Graphs: Updatable Views
Multiple Graphs: Updatable ViewsMultiple Graphs: Updatable Views
Multiple Graphs: Updatable ViewsopenCypher
 
1 chayes
1 chayes1 chayes
1 chayesYandex
 
Introduction to Graph neural networks @ Vienna Deep Learning meetup
Introduction to Graph neural networks @  Vienna Deep Learning meetupIntroduction to Graph neural networks @  Vienna Deep Learning meetup
Introduction to Graph neural networks @ Vienna Deep Learning meetupLiad Magen
 
Superworkflow of Graph Neural Networks with K8S and Fugue
Superworkflow of Graph Neural Networks with K8S and FugueSuperworkflow of Graph Neural Networks with K8S and Fugue
Superworkflow of Graph Neural Networks with K8S and FugueDatabricks
 
Analysis of Pathfinding Algorithms
Analysis of Pathfinding AlgorithmsAnalysis of Pathfinding Algorithms
Analysis of Pathfinding AlgorithmsSigSegVSquad
 
Tessellation on any_budget-gdc2011
Tessellation on any_budget-gdc2011Tessellation on any_budget-gdc2011
Tessellation on any_budget-gdc2011basisspace
 
Neo4j MeetUp - Graph Exploration with MetaExp
Neo4j MeetUp - Graph Exploration with MetaExpNeo4j MeetUp - Graph Exploration with MetaExp
Neo4j MeetUp - Graph Exploration with MetaExpAdrian Ziegler
 

Similar to Challenges in knowledge graph visualization (20)

Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
Neo4j Morpheus: Interweaving Table and Graph Data with SQL and Cypher in Apac...
 
Machine Learning and GraphX
Machine Learning and GraphXMachine Learning and GraphX
Machine Learning and GraphX
 
SCALABLE PATTERN MATCHING OVER COMPRESSED GRAPHS VIA DE-DENSIFICATION
SCALABLE PATTERN MATCHING OVER COMPRESSED GRAPHS VIA DE-DENSIFICATIONSCALABLE PATTERN MATCHING OVER COMPRESSED GRAPHS VIA DE-DENSIFICATION
SCALABLE PATTERN MATCHING OVER COMPRESSED GRAPHS VIA DE-DENSIFICATION
 
MapReduce Algorithm Design
MapReduce Algorithm DesignMapReduce Algorithm Design
MapReduce Algorithm Design
 
Multiple graphs in openCypher
Multiple graphs in openCypherMultiple graphs in openCypher
Multiple graphs in openCypher
 
Streaming Python on Hadoop
Streaming Python on HadoopStreaming Python on Hadoop
Streaming Python on Hadoop
 
Distributed graph processing
Distributed graph processingDistributed graph processing
Distributed graph processing
 
Computer Graphics - Lecture 01 - 3D Programming I
Computer Graphics - Lecture 01 - 3D Programming IComputer Graphics - Lecture 01 - 3D Programming I
Computer Graphics - Lecture 01 - 3D Programming I
 
Neo4j: Graph-like power
Neo4j: Graph-like powerNeo4j: Graph-like power
Neo4j: Graph-like power
 
Benchmarking Tool for Graph Algorithms
Benchmarking Tool for Graph AlgorithmsBenchmarking Tool for Graph Algorithms
Benchmarking Tool for Graph Algorithms
 
Multiple Graphs: Updatable Views
Multiple Graphs: Updatable ViewsMultiple Graphs: Updatable Views
Multiple Graphs: Updatable Views
 
1 chayes
1 chayes1 chayes
1 chayes
 
Introduction to Graph neural networks @ Vienna Deep Learning meetup
Introduction to Graph neural networks @  Vienna Deep Learning meetupIntroduction to Graph neural networks @  Vienna Deep Learning meetup
Introduction to Graph neural networks @ Vienna Deep Learning meetup
 
Hadoop classes in mumbai
Hadoop classes in mumbaiHadoop classes in mumbai
Hadoop classes in mumbai
 
Chord DHT
Chord DHTChord DHT
Chord DHT
 
Graph
GraphGraph
Graph
 
Superworkflow of Graph Neural Networks with K8S and Fugue
Superworkflow of Graph Neural Networks with K8S and FugueSuperworkflow of Graph Neural Networks with K8S and Fugue
Superworkflow of Graph Neural Networks with K8S and Fugue
 
Analysis of Pathfinding Algorithms
Analysis of Pathfinding AlgorithmsAnalysis of Pathfinding Algorithms
Analysis of Pathfinding Algorithms
 
Tessellation on any_budget-gdc2011
Tessellation on any_budget-gdc2011Tessellation on any_budget-gdc2011
Tessellation on any_budget-gdc2011
 
Neo4j MeetUp - Graph Exploration with MetaExp
Neo4j MeetUp - Graph Exploration with MetaExpNeo4j MeetUp - Graph Exploration with MetaExp
Neo4j MeetUp - Graph Exploration with MetaExp
 

More from GraphAware

Unparalleled Graph Database Scalability Delivered by Neo4j 4.0
Unparalleled Graph Database Scalability Delivered by Neo4j 4.0Unparalleled Graph Database Scalability Delivered by Neo4j 4.0
Unparalleled Graph Database Scalability Delivered by Neo4j 4.0GraphAware
 
Social media monitoring with ML-powered Knowledge Graph
Social media monitoring with ML-powered Knowledge GraphSocial media monitoring with ML-powered Knowledge Graph
Social media monitoring with ML-powered Knowledge GraphGraphAware
 
To be or not to be.
To be or not to be. To be or not to be.
To be or not to be. GraphAware
 
It Depends (and why it's the most frequent answer to modelling questions)
It Depends (and why it's the most frequent answer to modelling questions)It Depends (and why it's the most frequent answer to modelling questions)
It Depends (and why it's the most frequent answer to modelling questions)GraphAware
 
How Boston Scientific Improves Manufacturing Quality Using Graph Analytics
How Boston Scientific Improves Manufacturing Quality Using Graph AnalyticsHow Boston Scientific Improves Manufacturing Quality Using Graph Analytics
How Boston Scientific Improves Manufacturing Quality Using Graph AnalyticsGraphAware
 
When privacy matters! Chatbots in data-sensitive businesses
When privacy matters! Chatbots in data-sensitive businessesWhen privacy matters! Chatbots in data-sensitive businesses
When privacy matters! Chatbots in data-sensitive businessesGraphAware
 
Graph-Powered Machine Learning
Graph-Powered Machine LearningGraph-Powered Machine Learning
Graph-Powered Machine LearningGraphAware
 
Signals from outer space
Signals from outer spaceSignals from outer space
Signals from outer spaceGraphAware
 
Neo4j-Databridge: Enterprise-scale ETL for Neo4j
Neo4j-Databridge: Enterprise-scale ETL for Neo4jNeo4j-Databridge: Enterprise-scale ETL for Neo4j
Neo4j-Databridge: Enterprise-scale ETL for Neo4jGraphAware
 
Graph-Powered Machine Learning
Graph-Powered Machine Learning Graph-Powered Machine Learning
Graph-Powered Machine Learning GraphAware
 
(Big) Data Science
 (Big) Data Science (Big) Data Science
(Big) Data ScienceGraphAware
 
Modelling Data in Neo4j (plus a few tips)
Modelling Data in Neo4j (plus a few tips)Modelling Data in Neo4j (plus a few tips)
Modelling Data in Neo4j (plus a few tips)GraphAware
 
Intro to Neo4j (CZ)
Intro to Neo4j (CZ)Intro to Neo4j (CZ)
Intro to Neo4j (CZ)GraphAware
 
Modelling Data as Graphs (Neo4j)
Modelling Data as Graphs (Neo4j)Modelling Data as Graphs (Neo4j)
Modelling Data as Graphs (Neo4j)GraphAware
 
GraphAware Framework Intro
GraphAware Framework IntroGraphAware Framework Intro
GraphAware Framework IntroGraphAware
 
Advanced Neo4j Use Cases with the GraphAware Framework
Advanced Neo4j Use Cases with the GraphAware FrameworkAdvanced Neo4j Use Cases with the GraphAware Framework
Advanced Neo4j Use Cases with the GraphAware FrameworkGraphAware
 
Recommendations with Neo4j (FOSDEM 2015)
Recommendations with Neo4j (FOSDEM 2015)Recommendations with Neo4j (FOSDEM 2015)
Recommendations with Neo4j (FOSDEM 2015)GraphAware
 
Machine Learning Powered by Graphs - Alessandro Negro
Machine Learning Powered by Graphs - Alessandro NegroMachine Learning Powered by Graphs - Alessandro Negro
Machine Learning Powered by Graphs - Alessandro NegroGraphAware
 
Knowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe Willemsen
Knowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe WillemsenKnowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe Willemsen
Knowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe WillemsenGraphAware
 
The power of polyglot searching
The power of polyglot searchingThe power of polyglot searching
The power of polyglot searchingGraphAware
 

More from GraphAware (20)

Unparalleled Graph Database Scalability Delivered by Neo4j 4.0
Unparalleled Graph Database Scalability Delivered by Neo4j 4.0Unparalleled Graph Database Scalability Delivered by Neo4j 4.0
Unparalleled Graph Database Scalability Delivered by Neo4j 4.0
 
Social media monitoring with ML-powered Knowledge Graph
Social media monitoring with ML-powered Knowledge GraphSocial media monitoring with ML-powered Knowledge Graph
Social media monitoring with ML-powered Knowledge Graph
 
To be or not to be.
To be or not to be. To be or not to be.
To be or not to be.
 
It Depends (and why it's the most frequent answer to modelling questions)
It Depends (and why it's the most frequent answer to modelling questions)It Depends (and why it's the most frequent answer to modelling questions)
It Depends (and why it's the most frequent answer to modelling questions)
 
How Boston Scientific Improves Manufacturing Quality Using Graph Analytics
How Boston Scientific Improves Manufacturing Quality Using Graph AnalyticsHow Boston Scientific Improves Manufacturing Quality Using Graph Analytics
How Boston Scientific Improves Manufacturing Quality Using Graph Analytics
 
When privacy matters! Chatbots in data-sensitive businesses
When privacy matters! Chatbots in data-sensitive businessesWhen privacy matters! Chatbots in data-sensitive businesses
When privacy matters! Chatbots in data-sensitive businesses
 
Graph-Powered Machine Learning
Graph-Powered Machine LearningGraph-Powered Machine Learning
Graph-Powered Machine Learning
 
Signals from outer space
Signals from outer spaceSignals from outer space
Signals from outer space
 
Neo4j-Databridge: Enterprise-scale ETL for Neo4j
Neo4j-Databridge: Enterprise-scale ETL for Neo4jNeo4j-Databridge: Enterprise-scale ETL for Neo4j
Neo4j-Databridge: Enterprise-scale ETL for Neo4j
 
Graph-Powered Machine Learning
Graph-Powered Machine Learning Graph-Powered Machine Learning
Graph-Powered Machine Learning
 
(Big) Data Science
 (Big) Data Science (Big) Data Science
(Big) Data Science
 
Modelling Data in Neo4j (plus a few tips)
Modelling Data in Neo4j (plus a few tips)Modelling Data in Neo4j (plus a few tips)
Modelling Data in Neo4j (plus a few tips)
 
Intro to Neo4j (CZ)
Intro to Neo4j (CZ)Intro to Neo4j (CZ)
Intro to Neo4j (CZ)
 
Modelling Data as Graphs (Neo4j)
Modelling Data as Graphs (Neo4j)Modelling Data as Graphs (Neo4j)
Modelling Data as Graphs (Neo4j)
 
GraphAware Framework Intro
GraphAware Framework IntroGraphAware Framework Intro
GraphAware Framework Intro
 
Advanced Neo4j Use Cases with the GraphAware Framework
Advanced Neo4j Use Cases with the GraphAware FrameworkAdvanced Neo4j Use Cases with the GraphAware Framework
Advanced Neo4j Use Cases with the GraphAware Framework
 
Recommendations with Neo4j (FOSDEM 2015)
Recommendations with Neo4j (FOSDEM 2015)Recommendations with Neo4j (FOSDEM 2015)
Recommendations with Neo4j (FOSDEM 2015)
 
Machine Learning Powered by Graphs - Alessandro Negro
Machine Learning Powered by Graphs - Alessandro NegroMachine Learning Powered by Graphs - Alessandro Negro
Machine Learning Powered by Graphs - Alessandro Negro
 
Knowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe Willemsen
Knowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe WillemsenKnowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe Willemsen
Knowledge Graphs and Chatbots with Neo4j and IBM Watson - Christophe Willemsen
 
The power of polyglot searching
The power of polyglot searchingThe power of polyglot searching
The power of polyglot searching
 

Recently uploaded

Mission to Decommission: Importance of Decommissioning Products to Increase E...
Mission to Decommission: Importance of Decommissioning Products to Increase E...Mission to Decommission: Importance of Decommissioning Products to Increase E...
Mission to Decommission: Importance of Decommissioning Products to Increase E...Product School
 
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...Product School
 
Demystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John StaveleyDemystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John StaveleyJohn Staveley
 
The Future of Platform Engineering
The Future of Platform EngineeringThe Future of Platform Engineering
The Future of Platform EngineeringJemma Hussein Allen
 
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...Product School
 
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
 
Exploring UiPath Orchestrator API: updates and limits in 2024 🚀
Exploring UiPath Orchestrator API: updates and limits in 2024 🚀Exploring UiPath Orchestrator API: updates and limits in 2024 🚀
Exploring UiPath Orchestrator API: updates and limits in 2024 🚀DianaGray10
 
Key Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdfKey Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
 
In-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT ProfessionalsIn-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT ProfessionalsExpeed Software
 
"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
 
Knowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and backKnowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and backElena Simperl
 
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdfFIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdfFIDO Alliance
 
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptxUnpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptxDavid Michel
 
UiPath Test Automation using UiPath Test Suite series, part 2
UiPath Test Automation using UiPath Test Suite series, part 2UiPath Test Automation using UiPath Test Suite series, part 2
UiPath Test Automation using UiPath Test Suite series, part 2DianaGray10
 
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesAssuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesThousandEyes
 
НАДІЯ ФЕДЮШКО БАЦ «Професійне зростання QA спеціаліста»
НАДІЯ ФЕДЮШКО БАЦ  «Професійне зростання QA спеціаліста»НАДІЯ ФЕДЮШКО БАЦ  «Професійне зростання QA спеціаліста»
НАДІЯ ФЕДЮШКО БАЦ «Професійне зростання QA спеціаліста»QADay
 
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
 
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo DiehlFuture Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo DiehlPeter Udo Diehl
 
UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
 

Recently uploaded (20)

Mission to Decommission: Importance of Decommissioning Products to Increase E...
Mission to Decommission: Importance of Decommissioning Products to Increase E...Mission to Decommission: Importance of Decommissioning Products to Increase E...
Mission to Decommission: Importance of Decommissioning Products to Increase E...
 
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
 
Demystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John StaveleyDemystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John Staveley
 
The Future of Platform Engineering
The Future of Platform EngineeringThe Future of Platform Engineering
The Future of Platform Engineering
 
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
 
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
 
Exploring UiPath Orchestrator API: updates and limits in 2024 🚀
Exploring UiPath Orchestrator API: updates and limits in 2024 🚀Exploring UiPath Orchestrator API: updates and limits in 2024 🚀
Exploring UiPath Orchestrator API: updates and limits in 2024 🚀
 
Key Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdfKey Trends Shaping the Future of Infrastructure.pdf
Key Trends Shaping the Future of Infrastructure.pdf
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
 
In-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT ProfessionalsIn-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT Professionals
 
"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi
 
Knowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and backKnowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and back
 
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdfFIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdf
 
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptxUnpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx
 
UiPath Test Automation using UiPath Test Suite series, part 2
UiPath Test Automation using UiPath Test Suite series, part 2UiPath Test Automation using UiPath Test Suite series, part 2
UiPath Test Automation using UiPath Test Suite series, part 2
 
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesAssuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyes
 
НАДІЯ ФЕДЮШКО БАЦ «Професійне зростання QA спеціаліста»
НАДІЯ ФЕДЮШКО БАЦ  «Професійне зростання QA спеціаліста»НАДІЯ ФЕДЮШКО БАЦ  «Професійне зростання QA спеціаліста»
НАДІЯ ФЕДЮШКО БАЦ «Професійне зростання QA спеціаліста»
 
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
 
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo DiehlFuture Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
 
UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3UiPath Test Automation using UiPath Test Suite series, part 3
UiPath Test Automation using UiPath Test Suite series, part 3
 

Challenges in knowledge graph visualization

  • 1. Challenges in Knowledge Graph Visualization by GraphAware, world’s #1 Neo4j consultancy graphaware.com @graph_aware
  • 2. Speaker Jan Zak jan.zak@graphaware.com Twitter: @zakjan ● Senior Consultant at GraphAware ● data visualizations, maps, graphs
  • 3. ● not just lots of nodes, but also lots of node types with different levels of importance ● challenges of full visualization ○ rendering performance, layout quality ○ too many different colors hurts overview comprehensibility Knowledge Graph
  • 4. ● opposed to Search & Expand ● Ben Shneiderman: The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations ○ Visual Information-Seeking Mantra: Overview first, zoom and filter, then details-on-demand overview detail Overview & Detail-on-demand
  • 5. ● maps are graphs ○ real objects as nodes ○ neighbourhood connections as edges ● Overview & Detail-on-demand ○ configurable zoom level to display each object type ● yet, generic graphs are more complex ○ nodes position in visualization is not known before, must be computed by layout algorithm ○ nodes can be connected to any other nodes in the graph (possibly leading to supernodes) Analogy – Vector maps
  • 7. ● allows to create and return a virtual edge between any two nodes CALL apoc.create.vRelationship(n, 'TO', {}, m) APOC Virtual Edges
  • 8. ● all paths between a set of nodes MATCH (n:Outer) WITH collect(n) AS nodes CALL apoc.path.expandConfig(nodes, { terminatorNodes: nodes, maxLevel: 10 }) YIELD path AS p RETURN p ● before APOC Fall Release 3.5.0.5 ○ terminatorNodes + filterStartNode=false (default) was filtering out the terminator nodes ○ https://github.com/neo4j-contrib/neo4j-apoc-procedures/pull/1290 MATCH (n:Outer) WITH collect(n) AS nodes UNWIND nodes AS n WITH n, [m IN nodes WHERE n <> m] AS terminatorNodes CALL apoc.path.expandConfig(n, { terminatorNodes: terminatorNodes, maxLevel: 10 }) YIELD path AS p RETURN p APOC Path Expanders
  • 9. 1. Easy: Full render of huge graphs is not useful, because: A. technological limitation, slow rendering and layout performance B. comprehensibility limitation, too complex to extract insights from it C. both 2. Medium: How many max colors is recommended for a categorical measure? A. less than 10 B. less than 20 C. no limit 3. Hard: What’s the change in APOC Fall Release 3.5.0.5 in behavior of Path Expander? A. filterStartNode=false doesn’t filter terminationNodes anymore B. beginSequenceAtStart=false doesn’t filter terminationNodes anymore C. both Answer here: r.neo4j.com/hunger-games Hunger Games Questions for “Challenges in knowledge graph visualization”