3 ways that #DataVisualization will advance and impact users (including Knowledge Graphs): https://t.co/3XELwiVDDJ——————#BigData #DataScience #DataViz #VisualAnalytics #AnalyticsStrategy #DataStorytelling #KnowledgeGraphs #abdsc pic.twitter.com/N43Wx3APs2— Kirk Borne (@KirkDBorne) August 9, 2019

Graphileon joins CovidGraph, an initiative of graph enthusiasts and companies with the goal to build a knowledge graph with relevant information about the COVID-19 virus.

Because Graph Analytics is the future

For more complex products such as new pharmaceutical drugs, medical equipment or healthcare treatments, identifying hubs of influencers among physicians and other healthcare providers requires deep analysis of patient claims data to uncover the referral relationships.

Call records analysis with graph visualization.

How can companies step themselves into the world of graph databases? Neo4j thinks it has an answer. It has been offering a Startup Program for startups with 19 employees or fewer; more than 650 startups with fewer than 20 employees took advantage of having free access to Neo4j Enterprise clusters.

.@DDIAlliance releases XKOS v1.2 (Extended Knowledge Organization System) specification →facilitates sharing & management of statistical classifications.(For building #Semantic Taxonomies to tag Datasets & #DataScience outputs)https://t.co/HZD1nl5Nu0#BigData #Ontologies #RDF pic.twitter.com/DDYbHqCvm7— Kirk Borne (@KirkDBorne) June 21, 2019

When building graph data models we frequently have to deal with a degree of polymorphism for our entities just like the real world. For instance – I’m a person, but I’m also a parent, a spouse, a sibling, a child, a… Implicit categorisation Sometimes the entity categories are entirely defined by relationships to other entities. […]

Read the first installment of this blog series on artificial intelligence on the ways graph technology adds necessary context for powerful AI solutions.

Querying the first RDF Data Cube based on an existing PC-Axis/PX data cube published by @swissstatistics. Thanks to @bergi_bergos for the great converter, will be made public later pic.twitter.com/4SJ3jpKg7e— Adrian Gschwend (@linkedktk) July 10, 2019

Big data, semantic searches, and real-time responses are the reason behind the growing demand for graph databases. This article talks about what a graph database is, why graph databases are popular, and why and when we should use a graph database.

A comprehensive collection of recent papers on graph deep learning - DeepGraphLearning/LiteratureDL4Graph

Stardog 6.2 just shipped with scalable virtual graph caching, better Kubernetes integration, support for Amazon Redshift, and many new optimizations . Read on for the details.

This is what the resultant 100 retail outlet isochrone map looks like, built using Spatia and @rapidsai #cuGraph SSSP using @OrdnanceSurvey Open Roads as road graph + drive times estimated from @transportgovuk road stats #opendata cc @puntofisso pic.twitter.com/rGhDinkaVX— John Murray (@MurrayData) May 28, 2019

WHAT THIS TALK IS ABOUT My personal take on the history of human label collection ter to you

For a domain with a strong focus on unambiguous identifiers and meaning, the Semantic Web research field itself has a surprisingly ill-defined sense of identity. Started at the end of the 1990s at the intersection of databases, logic, and Web, and influenced along the way by all major tech hypes such as Big Data and machine learning, our research community needs to look in the mirror to understand who we really are…

Until now the only way to run Graph Algorithms on Neo4j has been to learn Cypher. The Graph Algorithms Playground changes all that.

After building and selling Heyzap back in 2016 I had free reign to dig into the question of “what should I really be working on?” and how to create something that would have a lasting impact on society. In part of this journey I’ve had the privilege to invest

It was hard to top last year’s demonstration of the new Microsoft 365 experienced powered by the Microsoft Graph. The focus this year shifted to how the graph could break down application and device silos to make everyday applications more user-centric.

One of Uber's experts in building knowledge graphs, Joshua Shinavier advises fellow data scientists that "real data is messy, but the fact is, if you want to build an enterprise knowledge graph, you have to deal with it."

Keynote talk given at the 41st European Conference on Information Retrieval (ECIR 2019)

Learn more about text-mined knowledge graphs and see how to build one with Grakn.

Grab your free copy of the brand new O'Reilly book, "Graph Algorithms: Practical Examples in Apache Spark & Neo4j" – a practical guide to graph analytics.

yWorks’ submission to the Graph Drawing Contest 2018 in Barcelona, Spain

All organisations find it difficult to fully describe their organisation in data. One of the most common pitfalls is underestimating the number of human-driven connections between data which have never been captured digitally.

does it support reverse direction edges?— Dan Brickley (@danbri) March 18, 2019