An Interactive Visualization Interface for Multidimensional Datasets
Repository: https://github.com/Collection-Space-Navigator/CSN
The Collection Space Navigator (CSN) is an explorative visualization tool for researching collections and their multidimensional representations. We designed this tool to better understand multidimensional data, its methods, and semantic qualities through spatial navigation and filtering. CSN can be used with any image collection and can be customized for specific research needs (see Jupyter Notebook or Google Colab).
The CSN code is partly based on the umap-explorer by GrantCuster.
🖥️ Online demo
📄 Paper on arxiv.org
🌐 Project website
We recommend using our colab: . It prepares the datasets and build a customized version of the Collection Space Navigator. For Jupyter Notebook, please use CSN_notebook.ipynb
Place your prepared dataset folders in the build/datasets
directory and modify build/datasets/datasets_config.json
. We recommend using our colab CSN_colab.ipynb
to format your data correctly.
To use the Collection Space Navigator locally run:
serve -s build
The CSN should be now accessible at http://localhost:3000
in your browser.
For development only.
Required: node.js
Important: node 16.16.0
is required! We recommend using NVM for node version managing:
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.3/install.sh | bash
export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")"
[ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh" # This loads nvm
nvm install v16.16.0
In the CSN
directory, run:
npm install
To run the development server:
npm start
Open http://localhost:3000 to view in your browser.
For production, run:
npm run build
It bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
See the section about deployment for more information.
@misc{ohm2023collection,
title={Collection Space Navigator: An Interactive Visualization Interface for Multidimensional Datasets},
author={Tillmann Ohm and Mar Canet Solà and Andres Karjus and Maximilian Schich},
year={2023},
eprint={2305.06809},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
Tillmann Ohm and Mar Canet Solà designed, co-authored, and developed the Collection Space Navigator (CSN) software. Tilmann Ohm, Mar Canet Solà, Anders Karjus, Maximilian Schich contributed to the broader research design, including initial applications of the CSN. The authors further thank the members of the CUDAN Research Group for useful discussions. All authors are supported by ERA Chair for Cultural Data Analytics, funded through the European Union’s Horizon 2020 research and innovation program (Grant No.810961).