Discover what's new in the Neo4j community for the week of 2 June 2018, including a new release of the Neo4j ETL Tool as well as a couple of new articles in our Graph Visualization series. Adam Hill’s talk about building a UK corporate interests graph is also online.

1. This Week in Neo4j

2. Developer Relations Engineer at Neo4j
2

3. The week's graph database news
in one handy slide deck!
Find the archive at
neo4j.com/tag/twin4j

4. Learn more about Dilyan

5. Watch the video
A few weeks ago I attended the PyData London 2018
conference and one of my favourite talks was by Adam Hill.
Adam gave an experience report of a DataKind UK and
Global Witness project where they built the world’s first
network graph mapping all of the UK
public data on those who control
corporate interests in the country.

6. Read about the release
On Thursday we released version 1.2.0 of the Neo4j ETL
Tool, a tool that makes it easy to convert your relational
data into a Neo4j graph. This version contains multi
schema support, additional driver support for Microsoft
SQL Server, IBM DB2 and Oracle RDBMS, as
well as general improvements
around the loading process.

7. Max De Marzi‘s shows how to take a PDF or text file, use
Apache Tika to detect and extract metadata and text, and
finally then run that text through a set of NLP models from
OpenNLP to find interesting Entities
which are then stored in Neo4j.
From document to graph

8. Combine yWorks and Neo4j
Sebastian Müller has written a blog post in which he shows
how to use yWorks and Neo4j to create high-quality graph
and diagram visualizations for end-user applications. You
can download a free evaluation
version of the yFiles for HTML
software package if you want to try
out the tool.

9. Download the slides
Gerrit Meier shared the slides from his talk at Spring IO in
which he explains how to build Spring backed applications
using Spring Data Neo4j.

10. Visualise all the things with Neo4j and Keylines
Dan Williams has written a post in which he explains how
to run a demo using Neo4j and Keylines. The examples uses
Cypher queries and KeyLines’ incremental layout to explore
a Neo4j dataset of movies
and actors.