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.
These can all be found on NL4DV's project website.
NL4DV is a collaborative project originally created by the Georgia Tech Visualization Lab at Georgia Institute of Technology with subsequent contributions from Ribarsky Center for Visual Analytics at UNC Charlotte and the DataVisards Group at The Hong Kong University of Science and Technology.
-
Georgia Tech Visualization Lab
- Arpit Narechania (currently at HKUST)
- Arjun Srinivasan
- Rishab Mitra
- Alex Endert
- John Stasko
-
Ribarsky Center for Visual Analytics at UNC Charlotte
-
DataVisards Group at The Hong Kong University of Science and Technology
- Arpit Narechania (previously at Georgia Tech)
-
Independent Contributor
- Tenghao Ji
We thank the members of the Georgia Tech Visualization Lab for their support and constructive feedback. We also thank @vijaynyaya for the inspiration to support multiple language model providers.
@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}
}@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}
}@misc{sah2024nl4dvllm,
title={Generating Analytic Specifications for Data Visualization from Natural Language Queries using Large Language Models},
author={{Sah}, Subham and {Mitra}, Rishab and {Narechania}, Arpit and {Endert}, Alex and {Stasko}, John and {Dou}, Wenwen},
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}
}@misc{ji2025nl4dvstylist,
title={{NL4DV-Stylist: Styling Data Visualizations Using Natural Language and Example Charts}},
author={{Ji}, Tenghao and {Narechania}, Arpit},
year={2025},
url={osf.io/fs4en_v1},
DOI={10.31219/osf.io/fs4en_v1},
publisher={OSF Preprints},
note={Presented as a poster at IEEE VIS 2025 (Poster Track)}
}The software is available under the MIT License.
If you have any questions, feel free to open an issue or contact Arpit Narechania.