Happy September!
We have a lot in store this week for Twin4j. First, we would like to remind you of the upcoming, live re-runs of the NODES 2021 workshops, scheduled for the week of September 13, 2021. All workshops are at a time that should be friendly to attendees of multiple time zones, and recordings will also be available if you cannot attend live.
We also have a variety of fun content this week, including knowledge graphs, using the Neo4j spatial capabilities to map out locations along a route, data lineage, and research with vaccinology. We also have a feature on a learning experiment to create a social network for bunnies.
Enjoy!
This week’s featured community member is Adnan Siddiqi.
Adnan Siddiqi – This Week’s Featured Community Member
Reminder: Neo4j Training Series September
We’re looking forward to having you join us on any (or all) sessions throughout the week!
Planning a Trip Through the State of New York with the AuraDB Free Tier
Have you ever thought about planning a route for a trip that includes where the rest stops are along the way, as well as pertinent details like which are handicap accessible or the closest one with a public phone? In the latest fun installment of “Discover Neo4j AuraDB Free with Lju and Alex” from
opens in new tabLju Lazarevic and
opens in new tabAlex Erdl, they explore a fun data set looking at the rest stops of the U.S. State of New York using the AuraDB Free tier coupled with
opens in new tabNeo4j spatial.
Enabling Data Lineage
Rapid data-driven decision making is clearly a key in enabling organizations to remain competitive. However, traditional data warehouses do not respond and adapt quickly and can limit the ability to make decisions quickly.
opens in new tabAmin Jalali recently wrote about his work on a new environment named Customer Analytics – Data Product Environment (CA-DPE), which is based on a data mesh approach. This environment provides several different “views” of each data product, such as reads, insertions, and deletions. This allows for each view to support the Create-Read-Update-Delete (CRUD) pattern for each data product. These data products and their relationships are generated in Neo4j, which allows for better understandability, transparency, traceability, and governance of the data.
LinkedImm: a Linked Data Graph Database for Integrating Immunological Data
opens in new tabSyed Ahmad Chan Bukhari has led a team of researchers to create a graph database for immunological data. Using Neo4j, his team created the publicly-available
opens in new tabLinkedImm knowledge graph, whose purpose is to facilitate vaccinology research. In their recent publication, the team points out that biological data is highly related and semi-structured, making graphs a much more suitable choice than traditional SQL databases. To help experimental immunologists get started using Cypher, a tool they might not be familiar with, they have created a web-based dashboard to allow interactions with their data either through ad-hoc queries or through spoken or typed natural language.
Bunnybook: a Social Network Built with FastAPI + React/RxJs, Neo4j, PostgreSQL, and Redis
Bite-Sized Neo4j for Data Scientists
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