Popular use cases for graph data

[draggett]

The aim of making RDF easier for the next 33% of developers begs the question of what are the popular application use cases for graph data (as a generalisation of RDF)? Here are some examples taken from graph database vendor websites.

Neo4J:
• Recommendation engines for e-commerce
• Network and database monitoring
• Fraud detection and analytics
• Social media and social networks
• Knowledge graphs for enhanced search services
• Identity and access management
• Privacy, risk and compliance
• Master data management
• Artificial Intelligence and analytics

Amazon Neptune:
• Network/IT operations
• Social networking
• Recommendation engines
• Fraud detection
• Knowledge graphs
• Life sciences

I am sure that this is just a few examples from a much much larger set. How can we reach out and gather information on use cases across different sectors, and the associated challenges facing application developers where new standards would help?

[maximveksler]

Cross linking semantalytics/awesome-semantic-web#32

[VladimirAlexiev]

• Intelligence/security (eg Palantir)
• Science knowledge graphs: for keeping the scientific record organized, for FAIR data and research, for open research, for new ways of tracking and analyzing the ever-exploding patent and publications domain, for recommendations, bibliometric analysis, etc (eg Microsoft Academic Graph, a great resource)
• Industry 4.0: complex engineering artefacts, maintenance info, parts databases (eg International Data Space, several auto makers, etc)
• Sensors
• Web of Things

[VladimirAlexiev]

http://sps.columbia.edu/executive-education/knowledge-graph-conference
Storing and Querying Knowledge Graphs
Formats and Languages
Metadata, Schemas, Ontologies, and Taxonomies
Data Governance
Data Quality
Linked-data
Master Data Management
Knowledge Graphs for AI
Natural Language Processing
Understanding Knowledge Graph Embeddings
Visualization
Search and Answer Engine Optimization
Applications in Healthcare, Finance, Media, and Open Data

https://www.eventbrite.com/e/2019-knowledge-graph-conference-tickets-54867900367 Knowlede Graphs everywhere:

• Digital Commerce
  Airbnb - Knowledge Graph at Airbnb
  Amazon - Deep Learning for Knowledge Extraction and Integration to build the Amazon Product Graph
  Uber - Building an Enterprise Knowledge Graph at Uber: Lessons from Reality
  Pitney Bowes (Single View Solutions) - Intelligent Customer Service Using Knowledge Graphs

• Financial Services
  Causality Link - A Perspective on the Reasoning Power of Knowledge Graphs
  Capital One - Knowledge Graph Pilot Provides Value
  Goldman Sachs - Pythia: the Goldman Sachs Social Graph
  TigerGraph - Analyzing Time-varying Transitive Risk in Swap Networks using Graphs
  Refinitiv Financial - Practical Use Cases and Challenges to Implement Graphs in Financial Services: Combating Financial Crime
  Wells Fargo - Knowledge Graphs and AI: The Future of Financial Data

• Health Care, Government, Supply Chain, Libraries
  AstraZeneca - Fair Data Knowledge Graphs (From Theory to Practice)
  Montefiore Hospital - The Chasm of a Million Analytics, and How to Bridge it?
  United Nations - A Graph as a Means to Store Unpredictable Knowledge – A Practical Implementation
  JSTOR Labs - Why Wikibase? Why not?
  Eccenca - Knowledge Graph for Digital Transformation in the Supply-Chain
  German National Library of Science and Technology - Creating a knowledge graph based Enterprise Innovation Architecture

• Forensics
  OCCRP - Using Graphs and Data Integration to Track Organised Crime
  Enigma.io - Impact and Insights from Public Data: Fighting Money Laundering by Linking and Resolving Entities
  Refinitiv Financial - Practical Use Cases and Challenges to Implement Graphs in Financial Services: Combating Financial Crime

• How To...
  Diffbot - Knowledge Graphs for AI
  Accenture Labs - Using a Domain Knowledge Graph to Manage AI at Scale
  Capsenta - Designing and Building Enterprise Knowledge Graphs from Relational Databases in the Real World
  Google AI - Wikidata, Knowledge Graphs, and Beyond
  IBM Research - Extending Knowledge Graphs using Distantly Supervised Deep Nets
  Microsoft - Building a Large-scale, Accurate and Fresh Knowledge Graph
  Neo4J - A Real-World Guide to Building Your Knowledge Graphs
  Collibra - Collibra's Context Graph

[izzykayu]

I would like to learn more about the difference between neo4j and other knowledge graph platforms such as ontotext. I work specifically in clinical natural language processing but leverage various clinical ontologies. hWhat is the difference between the formats and can both provide semantic relationships?