This Week in Neo4j: FOSDEM 2023 Sessions, Full Stack GraphQL, Data Importer Updates, dict2graph, NeoDash on Azure, and More

This week, check out the recorded livestream reviews of Will Lyon’s book, Full Stack GraphQL Applications, which is all about how to build web applications using GraphQL, React, Apollo, and Neo4j Database. Each episode of the Full Stack GraphQL Book Club series reviews a chapter of the book and works through the end-of-chapter exercises.

 The book is designed to show full stack developers how they can leverage the benefits of GraphQL, including GraphQL database integrations like the Neo4j GraphQL Library, cloud services like Netlify, AWS Lambda, Auth0, and Neo4j AuraDB.

Don’t forget to take advantage of the new series of technical workshops in March and April!

Yolande Poirier


Smita is Senior Manager, Cloud Data Architect and Graph Practice Lead, at Accenture. She is passionate about purpose-driven solutions using data and the cloud and enjoys exploring new technologies. She is pursuing her current area of interest as the AWS Innovation chapter lead and graph database practice lead. Connect with her on LinkedIn.

In her NODES 2022 presentation, “Knowledge Graphs Powering Active Metadata,” she discusses how to understand your data and build intelligent metadata. Watch her talk!

FOSDEM: Graph Systems and Algorithms DevRoom
Browse the videos and slides from talks at FOSDEM 2023, which took place in Brussels in February. In the graph category, some of the subjects were TEDective, exploring European public procurement data; the new HashGNN node embedding algorithm in GDS 2.3; and ipysigma, a Jupyter widget for interactive visual network analysis.
BOOK CLUB: 10 Things We Learned In Full Stack GraphQL
In a series of videos, William Lyon highlights some of the main takeaways of his book, Full Stack GraphQL Applications. The accompanying blog both summarizes and brings the book up to date by outlining the main points and explaining what was learned during the livestream.
NEO4J DATA IMPORTER: Introducing File Filtering
The latest release of Neo4j Data Importer introduces a new way to load more data sources without the need for pre-processing. If your CSV file contains several segments of data indicated by a different column value, you can now treat one file as several, creating separate nodes and relationships.
NODES SESSION: Keyword Disambiguation Using Transformers and Clustering to Build Cleaner Knowledge

Federica Ventruto and Alessia Melania Lonoce show you how the semantic similarity based on transformer embeddings and agglomerative clustering can help in the domain of academic disciplines and research fields. Learn how Neo4j improves the browsing experience of this knowledge graph.

DICT2GRAPH: A JSON to Neo4j Loading Tool

Tim Bleimehl at the German Center for Diabetes Research explains how dict2graph solves the problem of having to parse the specific JSON structure of each new data source. This open source module can load any JSON (or xml transformed to json) into a Neo4j database.

VISUALIZATION: Using NeoDash on Azure Web app for Containers

In an instructive blog enriched with code and screenshots, Paul Drangeid demonstrates how to host NeoDash on Azure with Docker. Once the application is created and configured, you can share your NeoDash reports from your Azure Cloud environment.

FACIAL RECOGNITION: An Evaluation of SQL and NoSQL Databases

Sefik Ilkin Serengil and Alper Ozpinar of Istanbul Ticaret University review the technical challenges of storage in facial recognition pipelines. They use graph databases and Graph Data Science centrality algorithms to detect false positives and false negatives in facial recognition.

TWEET OF THE WEEK: @PinkProgramming

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