This week Stefan Bieliauskas shows us how to model provenance data in Neo4j, and Lju Lazarevic takes us through some techniques for de-duplicating ingredients in the BBC Good Food Graph.
Featured Community Members: Ray Lukas
Our featured community members this week is Ray Lukas, Architect Advisor at CVS Health.
Ray Lukas – This Week’s Featured Community Member
His strong passion for connected data and understanding the complexities within our world, he began to create customized training materials on Neo4j development for his colleagues and friends.
He has a strong desire for helping people and contributing to an overall goal, which is what drove him to take on this pretty extensive project. His enthusiasm is infectious and he also happens to be an all around kind human. He’s a dog lover and has 4 collies!.
Thank you, Ray, for bringing positivity and excitement into our community! :heart:
Getting started with Provenance and Neo4j
In this week’s Neo4j Online Meetup, Stefan Bieliauskas shows us how to model provenance data using Neo4j.
You can also read the blog post that Stefan wrote on the same topic earlier this year.
What’s cooking? Part 5: Dealing with duplicates
In part 5 of the BBC Good Food series, Lju Lazarevic takes us through some techniques for de-duplicating ingredients.
Using only Cypher and the APOC library, Lju shows us how to find plurals that refer to the same thing, deal with active and passive naming, ignore stop words, deal with capitalisation issues, and more.
This Week in GRANDstack: GitHub Starter Template, StackOverflow API
And Michael Hunger wrote a blog post showing how to build a StackOverflow GraphQL API and Demo App in 10 Minutes.
ObservableHQ Notebook, Data Import with GraphXR, Redesigning Neo4j’s Developer Guides
- Sony Green shared the slides for his talk titled Data injection to Neo4j with GraphXR: Quick, easy, and code-free.
- We recently launched a revamp of Neo4j’s Developer guides, and Jennifer Reif has written about her experience working on this project.
Houston, we don’t have a problem – Understanding sentiment in space with NASA
David Meza, Chief Knowledge Architect at NASA, was interviewed by diginomica about his work building the lessons learned graph.
In the interview, David explains how his team made sense of unstructured data from NASA missions by combining natural language processing and graph approaches
Tweet of the Week
My favourite tweet this week was by Janos Szendi-Varga:
Don’t forget to RT if you liked it too.
That’s all for this week. Have a great weekend!