eren-ck / dg2pix

Pixel-Based Visual Analysis of Dynamic Graphs (VDS 2020 at IEEE VIS20)

dg2pix (dynamic graph to pixel-based visualization)

Pixel-Based Visual Analysis of Dynamic Graphs - [Paper]

Abstract

Presenting long sequences of dynamic graphs remains challenging due to the underlying large-scale and high-dimensional data. We propose dg2pix, a novel pixel-based visualization technique, to visually explore temporal and structural properties in long sequences of large-scale graphs. The approach consists of three main steps: (1) the multiscale modeling of the temporal dimension; (2) unsupervised graph embeddings to learn low-dimensional representations of the dynamic graph data; and (3) an interactive pixel-based visualization to simultaneously explore the evolving data at different temporal aggregation scales. dg2pix provides a scalable overview of a dynamic graph, supports the exploration of long sequences of high-dimensional graph data, and enables the identification and comparison of similar temporal states. We show the applicability of the technique to synthetic and real-world datasets, demonstrating that temporal patterns in dynamic graphs can be identified and interpreted over time. dg2pix contributes a suitable intermediate representation between node-link diagrams at the high detail end and matrix representations on the low detail end.

This repository provides a Python/Javascript implementation of dg2pix prototype as described in the paper:

@inproceedings{CaJaSc+2020dg2pix,
    author = {Cakmak, Eren and Jäckle, Dominik and Schreck, Tobias and Keim, Daniel A.},
    booktitle = {Symposium on Visualization in Data Science (VDS) at IEEE VIS 2020},
    title = {dg2pix: Pixel-Based Visual Analysis of Dynamic Graphs},
    year = {2020}
}

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How to locally run the prototype

1. Install Python requirements

pip install -r requirements.txt

2. Run app.py with Pyhton e.g.,

python3 app.py

3. Access the prototype implementation in the web browser

http://127.0.0.1:8000/

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How to locally develop the prototype

First, install the node.js modules and run wepack. Move the to the /frontend directory and run the following commands while working on the frontend:

npm install
npm run watch

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Datasets & Graph Embeddings

The following real-world dataset is currently used in the prototype Reddit Hyperlink Network. The graphs were embedded using the Karate Club library.

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License

Released under GNU General Public License v3.0. See the LICENSE file for details. The prototype was developed by Eren Cakmak from the Data Analysis and Visualization Group at the University Konstanz funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2117 – 422037984 and the European Union’s Horizon 2020 research and innovation programme under grant agreement No 830892.

dg2pix's Issues

ModuleNotFoundError: No module named 'sklearn.externals.joblib.parallel'

I just thought about making notice of the following:
app.py doesn't run only if scikit-learn is downgraded to 0.20.2.