Supports the creation of web-based data analytics dashboards consisting of linked views. Key features:

• Integrate different JavaScript visualization libraries (e.g., Vega-Lite, Plotly.js, Babylon.js)
• Thereby enable combination of InfoVis (e.g., scatter plot, parallel coordinates) and 3D views
• Specify layout and interactions with a JSON-based grammar

The recommended way of setting up your local Python environment is using conda. A good tutorial on using conda for managing Python environments can be found here.

Open a terminal (Linux) or Powershell (Windows) and check that conda is available:

conda --version

Note: If you did not add conda to the system PATH under Windows, you can us the the Anaconda Prompt (available in the start menu) instead of the Powershell.

In your terminal / Powershell / Anaconda Prompt navigate to this repository, create a new Python environment, and install the required packages.

cd <path-to-repository>
conda create --name coordinated-views python=3.8
conda activate coordinated-views
pip install -r requirements.txt

Navigate to repository, activate Python environment, and start data server (case study 1).

cd <path-to-repository>
conda activate coordinated-views
python data_server.py data/case_study_1

Data for case study 2 can be obtained here. To view the membrane potential on the dendrite additionally start the compute server:

conda activate coordinated-views
python compute_server.py data/case_study_2/simulation_data

Please refer to the documentation in the frontend folder.

Rapid Prototyping for Coordinated Views of Multi-scale Spatial and Abstract Data: A Grammar-based Approach. Philipp Harth, Arco Bast, Jakob Troidl, Bjorge Meulemeester, Hanspeter Pfister, Johanna Beyer, Marcel Oberlaender, Hans-Christian Hege, Daniel Baum. Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM), 2023.

Ion channel distributions in cortical neurons are optimized for energy-efficient active dendritic computations. Arco Bast, Marcel Oberlaender. bioRxiv 2021.12.11.472235; doi: https://doi.org/10.1101/2021.12.11.472235