Matches for: “visualization” …

Hubway Data Visualization Challenge with Neo4j

Michael Hunger imported the Hubway Challenge dataset into a Neo4j graph database, and made it available for us to play with.
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Graph Visualization and Neo4j – Part Three

Like I promised in my previous post, I wanted to do a little something on D3.js.

We are going to take one of their example visualizations and visualize a follows graph.

To create our graph, we will take the names of 20 people: create nodes for them, add them to an index, and randomly link them together.
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Graph Visualization and Neo4j – Part Two

If you’re into NoSQL and Graph Databases like Neo4j, then you’ll probably tend to be working on back-end development. If you’re lucky enough to work in a team of specialists, some UX guy will come up with user requirements, hand them off to a UI gal for design, who will then pass it on to a Javascript Ninja to slice it together and they’ll just ask you provide the data and stuff it in a JSON object.

If you’re not so lucky and are working on pet projects by yourself then you’ll have to do it all. So I wanted to give you a little nudge into learning a visualization framework. Since my most popular blog post so far has been Graph Visualization and Neo4j and we’ve already seen one example that you’ll probably want to customize in your projects, we’ll stick with processing.js, and in the future I can do a little intro on D3.js, Unveil.js and maybe something a little crazier like VVVV.js.

So getting started is really easy. We’ll create an html document, add the minified processing javascript library and create a canvas element to put our visualization.

<!DOCTYPE html>
		<title>Hello World - Processing.js</title>
		<script src="processing-1.3.6.min.js"></script>
		<canvas data-src="helloworld.pjs"></canvas>

All right, let’s create the helloworld.pjs we reference as our canvas data source.
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Graph Visualization and Neo4j

So far we’ve learned how to get Neo4j up and running with Neography, how to find friends of friends and degrees of separation with the Neo4j REST API and a little bit of the Gremlin and Cypher languages. However, all we’ve seen is text output. We haven’t really “seen” a graph yet, but that’s about to change.

Vouched holds a graph of skill specific recommendations people have made to each other and visualizes it. I extracted the visualization, and hosted it on github as neovigator. You can get your very own visualization up and running or take a look at this instance running on Heroku.

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Visualizing Activities

A few weeks ago I blogged about Activities in Neo4j, and we ended up with a way to recommend an activity to a user based on what sequence of activities they had done in the past. We also had a list of common sequences of activities, but they were a bit hard to digest. Today I’m going to show you how to visualize them so they make more sense.

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Our own Multi-Model Database – Part 5


In part 4 I promised metrics and a shell, so that’s what we’ll tackle today. We are lucky that the Metrics library can be plugged into Jooby without much effort… and double lucky that the Crash library can also be plugged into Jooby without much effort. This is what we are all about here because we’re a bunch of lazy, impatient developers who are ignorant of the limits of our capabilities and who would rather reuse open source code instead of falling victim to the “Not Invented Here” syndrome and do everything from scratch.
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Giving Neo4j 2.2 a Workout


Neo4j 2.2 is getting released any day now, so let’s put the Release Candidate through its paces with Gatling. Once we download and start it up, you’ll notice it wants us to authenticate.
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Tracking User Paths in an IVR with Neo4j

I started my software development career writing applications for a Call Center at a small bank in Florida. I remember the bank had purchased whatever the “Cadillac” of Interactive Voice Response (IVR) systems was then for some crazy amount of money. Today you can build an IVR overnight using Twilio.


When you sign up with Twilio, you get to choose your phone number (more or less). For example, I picked +1 (636) 451-7411, which spells out +1 (neo) 4j1-7411. If you were to call this number right now (assuming I have not run out of Twilio credits) you’ll connect to my IVR.
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The Last Mile


The “last mile” is a term used in the telecommunications industry that refers to delivering connectivity to the customers that will actually be using the system. In the sense of Graph Databases, it refers to how well the end user can extract value and insight from the graph. We’ve already seen an example of this concept with Graph Search, allowing a user to express their requests in natural language. Today we’ll see another example. We’ll be taking advantage of the features of Neo4j 2.0 to make this work, so be sure to have read the previous post on the matter.

We’re going to be using VisualSearch.js made by Samuel Clay of NewsBlur. VisualSearch.js enhances ordinary search boxes with the ability to autocomplete faceted search queries. It is quite easy to customize and there is an annotated walkthrough of the options available. You can see what it does in the image below, or click it to try their demo.

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Visualizing the news with Vivagraph.js


Today I want to introduce you to VivaGraphJS – a JavaScript Graph Drawing Library made by Andrei Kashcha of Yasiv. It supports rendering graphs using WebGL, SVG or CSS formats and currently supports a force directed layout. The Library provides an API which tracks graph changes and reflect changes on the rendering surface which makes it fantastic for graph exploration.

Today we will be integrating it with Neo4j and the Alchemy API.

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