Showing posts from 2014

Anatomy of an Emerging Knowledge Network: The Zapnito Graph Vizualized

In this article, I take a high-level look Zapnito, a multi-tenant "Networked Knowledge" platform designed around small, expert communities.

Zapnito is a knowledge sharing platform that allows organizations to create branded networks of experts. It's aimed at publishers, consultancies, media companies, and other corporations. Zapnito includes some social features (such as follow relationships, collaboration), but its focus is knowledge sharing rather than social networking.

As the founder puts it: "Zapnito is a white label platform that offers knowledge network capabilities for publishers. We provide both highly private and open networks, and we own neither publisher content or associated data - both of these are retained by publishers." 

The aim of this article is to show some of the interesting insights that can be gained from basic Social Network Analysis (SNA) of Zapnito. I'll be showing visualizations (such as that on the right) built from an anonymiz…

I Know Where You Were Last Summer: London's public bike data is telling everyone where you've been

This article is about a publicly available dataset of bicycle journey data that contains enough information to track the movements of individual cyclists across London, for a six month period just over a year ago.

I'll also explore how this dataset could be linked with other datasets to identify the actual people who made each of these journeys, and the privacy concerns this kind of linking raises.


It probably won't surprise you to learn that there is a publicly available Transport For London dataset that contains records of bike journeys for London's bicycle hire scheme. What may surprise you is that this record includes unique customer identifiers, as well as the location and date/time for the start and end of each journey. The public dataset currently covers a period of six months between 2012 and 2013.

What are the consequences of this? It means that someone who has access to the data can extract and analyse the journeys made by individual cyclists within London du…

London maps and bike rental communities, according to Boris Bike journey data

Every time someone in London makes a journey on a Boris Bike (officially, the Barclays Cycle Hire Scheme), the local government body Transport For London (TFL) record that journey. TFL make some of this data available for download, to allow further analysis and experimentation.

Below, you'll find maps of the most popular bike stations and routes in London, created from the TFL data using Gephi, plus a few simple data processing scripts that I threw together. The idea for these maps originated within a project group at a course on Data Visualisation, held at the Guardian last year. We're working on a more publisher friendly form, so thank you to my course mates for giving me the go ahead to include them here.

First, here's a map showing all bike stations and all popular journeys.

The first map shows the most popular routes and bike stations, those with more than ~150 journeys made during the six months of data that TFL make available. The size of each bike station in this m…