ICAT
ICAT: The Interactive Corpus Analysis Tool - Published in JOSS (2025)
Science Score: 96.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 2 DOI reference(s) in README and JOSS metadata -
✓Academic publication links
Links to: acm.org, joss.theoj.org -
○Academic email domains
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✓Institutional organization owner
Organization ornl has institutional domain (software.ornl.gov) -
✓JOSS paper metadata
Published in Journal of Open Source Software
Scientific Fields
Repository
Interactive machine learning dashboard for textual data exploration
Basic Info
- Host: GitHub
- Owner: ORNL
- License: bsd-3-clause
- Language: Python
- Default Branch: main
- Homepage: https://ornl.github.io/icat/
- Size: 3.71 MB
Statistics
- Stars: 4
- Watchers: 3
- Forks: 1
- Open Issues: 18
- Releases: 14
Metadata Files
README.md
Interactive Corpus Analysis Tool
The Interactive Corpus Analysis Tool (ICAT) is an interactive machine learning (IML) dashboard for unlabeled text datasets that allows a user to iteratively and visually define features, explore and label instances of their dataset, and train a logistic regression model on the fly as they do so to assist in filtering, searching, and labeling tasks.
ICAT is implemented using holoviz's panel library, so it can either directly be rendered like a widget in a jupyter lab instance, or incorporated as part of a standalone panel website.
Installation
ICAT can be installed via pip with:
pip install icat-iml
Documentation
The user guide and API documentation can be found at https://ornl.github.io/icat.
Visualization
The primary ring visualization is called AnchorViz, a technique from IML literature. (See Chen, Nan-Chen, et al. "AnchorViz: Facilitating classifier error discovery through interactive semantic data exploration")
We implemented an ipywidget version of AnchorViz and use it in this project, it can be found separately at https://github.com/ORNL/ipyanchorviz
Contributing
Contributions for improving ICAT are welcome! If you run into any problems, find bugs, or think of useful improvements and enhancements, feel free to open an issue.
If you add a feature or fix a bug yourself and want it considered for integration, feel free to open a pull request with the changes. Please provide a detailed description of what the pull request is doing and briefly list any significant changes made. If it's in regards to a specific issue, please include or link the issue number.
Citation
To cite usage of ICAT, please use the following bibtex:
bibtex
@misc{doecode_105653,
title = {Interactive Corpus Analysis Tool},
author = {Martindale, Nathan and Stewart, Scott},
abstractNote = {The Interactive Corpus Analysis Tool (ICAT) is an interactive machine learning dashboard for unlabeled text/natural language processing datasets that allows a user to iteratively and visually define features, explore and label instances of their dataset, and simultaneously train a logistic regression model. ICAT was created to allow subject matter experts in a specific domain to directly train their own models for unlabeled datasets visually, without needing to be a machine learning expert or needing to know how to code the models themselves. This approach allows users to directly leverage the power of machine learning, but critically, also involves the user in the development of the machine learning model.},
year = {2023},
month = {apr}
}
Owner
- Name: Oak Ridge National Laboratory
- Login: ORNL
- Kind: organization
- Email: software@ornl.gov
- Location: Oak Ridge TN
- Website: http://software.ornl.gov
- Repositories: 99
- Profile: https://github.com/ORNL
Software repositories from Oak Ridge National Laboratory
JOSS Publication
ICAT: The Interactive Corpus Analysis Tool
Authors
Oak Ridge National Laboratory
Oak Ridge National Laboratory
Editor
Josh Borrow
Tags
Machine Learning HCI Visual AnalyticsGitHub Events
Total
- Create event: 2
- Release event: 2
- Issues event: 4
- Issue comment event: 5
- Push event: 15
Last Year
- Create event: 2
- Release event: 2
- Issues event: 4
- Issue comment event: 5
- Push event: 15
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 48
- Total pull requests: 1
- Average time to close issues: about 1 month
- Average time to close pull requests: 1 day
- Total issue authors: 5
- Total pull request authors: 1
- Average comments per issue: 0.65
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 5
- Pull requests: 0
- Average time to close issues: 21 days
- Average time to close pull requests: N/A
- Issue authors: 3
- Pull request authors: 0
- Average comments per issue: 0.8
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- WildfireXIII (39)
- WarmCyan (4)
- JBorrow (2)
- jhagerer (1)
- SamHames (1)
Pull Request Authors
- WildfireXIII (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 40 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 15
- Total maintainers: 2
pypi.org: icat-iml
Interactive Corpus Analysis Tool
- Homepage: https://github.com/ORNL/icat
- Documentation: https://ornl.github.io/icat/
- License: BSD License
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Latest release: 0.8.1
published 7 months ago
Rankings
Maintainers (2)
Dependencies
- actions/checkout v3 composite
- actions/configure-pages v3 composite
- actions/deploy-pages v2 composite
- actions/upload-pages-artifact v2 composite
- actions/checkout v3 composite
- actions/setup-python v2 composite
- pre-commit/action v3.0.0 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- altair *
- build *
- ipyanchorviz *
- ipyvuetify *
- ipywidgets *
- numpy *
- pandas *
- panel *
- pre-commit *
- pydata-sphinx-theme *
- pytest *
- pytest-mock *
- scikit-learn *
- sphinx *
- sphinx-favicon *
- twine *
- altair *
- ipyanchorviz *
- ipyvuetify *
- ipywidgets *
- numpy *
- pandas *
- panel *
- scikit-learn *
- ipyvuetify
- ipywidgets
- jupyter
- jupyterlab
- nodejs
- numpy
- pandas
- panel
- pytest
- pytest-mock
- python 3.10.*
- scikit-learn