Software, startups, and data
Google's Open Knowledge Format (OKF) is already a graph - it's just serialized as markdown files. Here's how to materialize OKF bundles in Neo4j and build GraphRAG that never serves deprecated knowledge unlabeled: trust tiers, staleness, impact analysis, and retrieval with the graph in the loop.
Vercel's Eve framework makes durable agents easy - but agents still forget. Here's how I gave one persistent, graph-native memory using the Neo4j Agent Memory Service (NAMS), built around a real National Parks trip-planner called TrailGraph.
A complete guide to deploying Neo4j Enterprise 5.x on any VPS (Digital Ocean, AWS, GCP, Azure, or on-premises) with SSL/TLS encryption, database restoration, and read-only user configuration.
Building interactive graph visualizations with Sigma React - from basic setup to advanced customizations
Using aerial imagery and Spatial SQL to explore Forest Service road networks
My take on the exciting world of spatial database technology plus a look at getting started with Apache Sedona.
A look at loading points of interest from the Overture Maps public dataset into the Neo4j graph database, plus writing Spatial SQL queries with AWS Athena.
A resource for working with geospatial data in Neo4j.
Radius Distance, Bounding Box, and Point in Polygon Search With Graphs
Building Interactive Graph Data Visualizations With GraphQL
Using Next.js API Routes And Deploying To Vercel & Neo4j Aura
Using The Flat Data GitHub Action To Import Data From The Lobste.rs News Site
Building A GRANDstack Podcast App: Episode 6
Building A GRANDstack Podcast App: Episode 5
Building A GRANDstack Podcast App: Episode 4
Building A GRANDstack Podcast App: Episode 3
Building A GRANDstack Podcast App: Episode 2
Building A GRANDstack Podcast App: Episode 1
Using low code graph apps to build data visualizations with Neo4j.
Using the new Jolt format with HTTP in Neo4j 4.2 with edge network handlers.
This post explores how to build spatial data visualizations using address data from the Paradise Papers leak of offshore corporations and the people connected to them. First, we geocode all addresses in the leaked data, then build a heatmap and interactive map for exploring the data of offshore legal entities.
Natural language processing (NLP) techniques like entity extraction can be used to help make sense of a large text corpus. In this post we apply named entity resolution to the scraped Russian Twitter Troll tweets to try to get a better understanding of how these trolls were spreading fake news.
In this post we explore how to scrape tweets from Internet Archive for Russian Twitter Troll accounts, import into Neo4j for analysis, and how to build a simple GraphQL API exposing the data through GraphQL.
Many web services are converting their publicly facing APIs from REST to GraphQL. Companies like GitHub and Shopify have been leading this transition to GraphQL. In this post we take a look at how we can query the new Mattermark GraphQL API using Apollo Client, storing the results in Neo4j to then see what we can learn about a local startup ecosystem.
One of the powers of working with graph databases is the ability to combine disparate datasets and query across them. Today we will look at how we can combine the BuzzFeed Trumpworld graph with data about federal government contracts from USASpending.gov, allowing us to examine any government contracts that were awarded to organizations that appear in Trumpworld.
Updating legis-graph-spatial to make use of the new spatial procedures in Neo4j 3.0 and the official Neo4j Javascript driver. Procedures provide a new API for interacting with the Neo4j spatial extension and are callable from Cypher.
Using graphs to analyze character interactions in the popular Game of Thrones series. Social network analysis with Neo4j.
Adding geospatial indexing and map visualizations to legis-graph
Finding real world text datasets to analyze can make playing around with NLP tasks much more interesting. This quick post shows how to build a word adjacency graph in Neo4j using product reviews from the Best Buy API.
A common task when working with data from APIs is crawling the API and inserting the results in a database. In this example we will import data into Neo4j by crawling a public API, building a graph in Neo4j as we go along. We will use Neo4j as a queuing mechanism to store URLs for placeholder resources waiting to be fetched.
This post shows how we can apply graph analytics to US Congressional data to find influential legislators in Congress. Using the Mazerunner open source graph analytics project we are able to use Apache Spark GraphX alongside Neo4j to run the PageRank algorithm on a collaboration graph of US Congress.
Interactions among members of any large organization are naturally a graph, yet the tools we use to analyze data about these organizations often ignore the graphiness of the data and instead map the data into structures (such as relational databases) that make taking advantage of the relationships in the data much more difficult when it comes time to analyze the data. Collaboration networks are a…
Discovering paradigmatic word associations is one of the core tasks of Natural Language Processing. In this post we explore a graph based method for mining paradigmatic word associations from a text corpus.
Using article links shared on Twitter to determine user interests, we show how to build a personalized content recommender system to suggest other articles the user might be interested in.
We show how to load data from the Yelp Academic Dataset into Neo4j, then build a webapp to perform geospatial queries on the data and visualize the results on a map.
What have I been doing in Santiago Chile as part of Startup Chile? I share some of my experiences from Startup Chile Generation 11.
GraphConnect is an annual conference for graph database enthusiasts. These are my notes from GraphConnect 2014 in San Francisco.
My experiences during Boulder StartupWeek 2014.
Loading every airport in the world into Neo4j Spatial for the purposes of route finding.
A system for ranking tweets based on user affinity and time decay.
Using data about global militarized interstate disputes (wars) we build some geospatial visualizations to analyze data about war fatalities throughout history.