D3-projects

Visualization of a network using D3.js

Data visualization of a conference network using D3.js library

The data

Format and purpose of the data

1. The data represents the users and papers of a conference;

2. The data itself is originated from the .gdf file inside data/;

3. This .gdf is pre-processed (see below) and transformed into a .json with additional information.

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Data pre-processing

Done once, prepares the data for the visualization front-end and creates the .json.

1. The data directory contains scripts for data pre-processing;

2. process_data is a python script to run the whole pre-processing;

3. The clustering directory has all the necessary intermediate files created by process_data and the k-means clustering C program and source code in ./data/clustering/program;

4. More info in data/README.md.

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Data real-time processing and visualization

Done in real time, for every user.

1. D3.js is responsible for the real-time data retrieving and rendering;

2. The data is obtained from ./data/data.json using the ./scripts/ex4.js script;

3. The JavaScript should be called by ./demo.html by running a local server, for example. Note that it may not work by opening demo.html with a browser, because external files are required;

4. A few screenshots of the visualization working can be found in ./samples/;

5. The D3 visualization chosen is the Hierarchical Edge Bundling.

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Lucas Parzianello - 2016