Welcome to this week in Neo4j where we round up what’s been happening in the world of graph databases in the last 7 days.
Neo4j GraphTour is here
We’ll also be running GraphClinics at each event where you can come and ask Neo4j engineers for one-on-one help with your project and get all your graph related questions answered.
Michael Hunger or I will be at each event and will be presenting Utilizing Powerful Extensions for Analytics & Operations where we’ll show how you how to supercharge your Neo4j experience.
There are still seats available for some of the events but don’t procrastinate too long, register now!
Featured Community Member: Tim Williamson
This week’s featured community member is Tim Williamson, Data Scientist and Associate Fellow at Monsanto Company.
Tim Williamson – This Week’s Featured Community Member
Tim has been a member of the Neo4j community for several years now and is a strong advocate for graphs on social media, frequently helping people out with their graph questions.
I first came across Tim during his presentation Graphs Are Feeding The World at GraphConnect SF 2015, which he then followed up with a 5 minute interview. You can also find the slides from Tim’s talk.
Tim also presented Using Graph Databases to Operationalize Insights from Big Data at Strata 2016 with Neo4j CEO Emil Eifrem.
On behalf of the Neo4j community, thanks for all your work Tim!
Online Meetup: Data Science in Practice: Importing and Visualizing Facebook Using Graphs
In this week’s online meetup Ray Barnard and Jen Webb from Suprfanz showed us how to import Facebook events into Neo4j and visualise them using d3.js.
They guided us through a Python based tutorial which you can find in the suprfanz/flask-fb-neo4j-d3 GitHub repository.
Pick of the week: Reactome – Efficient access to complex pathway data
Reactome – Efficient access to complex pathway data
Reactome annotates processes in a consistent pathway model to create a resource for researchers as a core reusable pathway dataset for systems biology approaches. It also provides infrastructure and bioinformatics tools for search, visualisation, interpretation and analysis of pathways
In the paper the authors explain how they were able to use Neo4j and Cypher to greatly improve query efficiency, reducing the average query time by 93% from when they stored the data in MySQL.
APOC, ETL Tool, Google Cloud Functions
- Chris Skardon has started writing a Better Know APOC series of posts on the popular library. In the first post Chris shows how to install APOC and explains the basic structure of all its procedures. He then has a post looking at the procedures available for exporting data from Neo4j.
- David Allen wrote Capturing and Integrating Service Data with Google Cloud Functions and Neo4j. He also shared the Google Cloud functions mentioned in the post in the neo4j-serverless-functions repository.
- Praveena Fernandes presented a webinar – Interpreting Relational Schema to Graphs – in which she showed how to use the ETL Tool from the Neo4j Desktop. You can also view Praveena’s slides.
- A question on StackOverflow about bidirectional relationships led me to rediscover a timeless article written by Michal Bachman back in 2013 where he covers this topic in detail.
On the Podcast: Laura Drummer
They talk about Laura’s work building social networks of not only people, but also things that they’re talking about. Laura explains how she’s been able to use Python Data Science tools scikit-learn and gensim to build these graphs.
Laura presented the talk Sentiment and Social Network Analysis at GraphConnect NYC 2017 so I’d recommend watching that if you want to learn more.
What’s happening next week in the world of graph databases?
February 12th 2017
Shahar Shaked, Mark Needham
February 13th 2017
Mix of Neo4j and customer speakers
February 14th 2017
February 15th 2017
Mix of Neo4j and customer speakers
Tweet of the Week
My favourite tweet this week was by Bill J. Stidham:
Don’t forget to RT if you liked it too.
That’s all for this week. Have a great weekend!