NL4DV is a Python toolkit that takes a natural language (NL) query about a given dataset as input and outputs a structured JSON object containing Data attributes, Analytic tasks, and Visualizations (Vega-Lite specifications).
Project description
NL4DV: Natural Language toolkit for Data Visualization
NL4DV takes a natural language query about a given dataset as input and outputs a structured JSON object containing:
- Data attributes,
- Analytic tasks, and
- Visualizations (Vega-Lite specifications)
With this output, developers can
- Create visualizations in Python using natural language, and/or
- Add a natural language interface to their existing visualization systems.
Setup Instructions, API Documentation, and Examples
These can all be found on NL4DV's project website.
Credits
NL4DV was created by Arpit Narechania, Arjun Srinivasan, Rishab Mitra, Alex Endert, and John Stasko of the Georgia Tech Visualization Lab. Along with Subham Sah, and Wenwen Dou of the Ribarsky Center for Visual Analytics at UNC Charlotte.
We thank the members of the Georgia Tech Visualization Lab for their support and constructive feedback.
Citations
2021 IEEE TVCG Journal Full Paper (Proceedings of the 2020 IEEE VIS Conference)
@article{narechania2021nl4dv,
title = {{NL4DV}: A {Toolkit} for Generating {Analytic Specifications} for {Data Visualization} from {Natural Language} Queries},
shorttitle = {{NL4DV}},
author = {{Narechania}, Arpit and {Srinivasan}, Arjun and {Stasko}, John},
journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG)},
doi = {10.1109/TVCG.2020.3030378},
year = {2021},
publisher = {IEEE}
}
2022 IEEE VIS Conference Short Paper Track
@inproceedings{mitra2022conversationalinteraction,
title = {{Facilitating Conversational Interaction in Natural Language Interfaces for Visualization}},
author = {{Mitra}, Rishab and {Narechania}, Arpit and {Endert}, Alex and {Stasko}, John},
booktitle={2022 IEEE Visualization Conference (VIS)},
url = {https://doi.org/10.48550/arXiv.2207.00189},
doi = {10.48550/arXiv.2207.00189},
year = {2022},
publisher = {IEEE}
}
2024 IEEE VIS NLVIZ workshop Paper
@misc{sah2024nl4dvllm,
title={Generating Analytic Specifications for Data Visualization from Natural Language Queries using Large Language Models},
author={Subham Sah and Rishab Mitra and Arpit Narechania and Alex Endert and John Stasko and Wenwen Dou},
year={2024},
eprint={2408.13391},
archivePrefix={arXiv},
primaryClass={cs.HC},
url={https://arxiv.org/abs/2408.13391},
howpublished={Presented at the NLVIZ Workshop, IEEE VIS 2024}
}
License
The software is available under the MIT License.
Contact
If you have any questions, feel free to open an issue or contact Arpit Narechania.
Project details
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