Data visualization of a conference network using D3.js library
-
The data represents the users and papers of a conference;
-
The data itself is originated from the
.gdf
file insidedata/
; -
This
.gdf
is pre-processed (see below) and transformed into a.json
with additional information.
-
The
data
directory contains scripts for data pre-processing; -
process_data
is a python script to run the whole pre-processing; -
The
clustering
directory has all the necessary intermediate files created byprocess_data
and the k-means clustering C program and source code in./data/clustering/program
; -
More info in
data/README.md
.
-
D3.js is responsible for the real-time data retrieving and rendering;
-
The data is obtained from
./data/data.json
using the./scripts/ex4.js
script; -
The JavaScript should be called by
./demo.html
by running a local server, for example. Note that it may not work by openingdemo.html
with a browser, because external files are required; -
A few screenshots of the visualization working can be found in
./samples/
; -
The D3 visualization chosen is the Hierarchical Edge Bundling.