https://github.com/sintel-dev/mtv
A Full-stack Platform for Multiple Time-series Visualization (MTV) and Anomaly Analysis.
https://github.com/sintel-dev/mtv
anomaly-detection data-analysis visualization
Last synced: 10 months ago
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A Full-stack Platform for Multiple Time-series Visualization (MTV) and Anomaly Analysis.
- Host: GitHub
- URL: https://github.com/sintel-dev/mtv
- Owner: sintel-dev
- License: mit
- Created: 2018-11-15T15:26:07.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2024-02-10T05:42:07.000Z (almost 2 years ago)
- Last Synced: 2025-03-24T19:21:45.204Z (10 months ago)
- Topics: anomaly-detection, data-analysis, visualization
- Language: TypeScript
- Homepage: https://github.com/signals-dev/MTV
- Size: 20.8 MB
- Stars: 11
- Watchers: 3
- Forks: 2
- Open Issues: 32
-
Metadata Files:
- Readme: README.md
- Changelog: HISTORY.md
- License: LICENSE
Awesome Lists containing this project
README
An open source project from Data to AI Lab at MIT.
[](https://coveralls.io/github/dyuliu/MTV)
[](https://github.com/dyuliu/MTV/releases)
[](https://hub.docker.com/r/dyuliu/mtv)
# MTV
**MTV** is a visual analytics system built for anomaly analysis of multiple time-series data.
## License
[The MIT License](https://github.com/HDI-Project/MTV/blob/master/LICENSE)
## Prerequisites
Make sure you have installed all of the following prerequisites on your development machine:
- **Sintel** - MTV is the visual interface that requires running sintel as the backend. Please install [Sintel](https://github.com/sintel-dev/sintel) first if you want to try the full feature of MTV.
- **Node.js (>= 10.0.0)** - [Download & Install Node.js](https://nodejs.org/en/download/) and the npm package manager. Make sure to install gulp-cli globally after the installation of Node.js.
## Get Started
### Install
Download the repository
```bash
$ git clone https://github.com/sintel-dev/MTV mtv
```
Once you've downloaded the MTV repository and installed all the prerequisites, you're just a few steps away from running your application. To install the project, create a virtualenv and execute
```bash
$ npm install
```
To avoid version conflicts and dependency issues, we have locked the versions of all packages and their dependencies in `package-lock.json`. The execution of the `npm install` command will, by default, install all packages using exactly the same versions specified in the `package-lock.json`.
### Running Your Application
#### 1. Run Sintel as the backend
Please make sure Sintel runs on the port 3000. If not, you can change the config in the file `src/model/utils/constants.tsx` to ensure that MTV is able to connect to Sintel correctly.
#### 2. Build MTV
```bash
$ npm run build
```
#### 3. Launch it
```bash
$ npm run serve
```
Your application should run on **port 4200** with the **_production_** environment by default. Just go to [http://localhost:4200](http://localhost:4200) in your browser (Chrome recommended).
### Development
If you want to make changes on the interface and customize it to your own application scenario, you can run the following command:
```bash
$ npm start
```
Everytime you make changes on the source code, the interface will be automatically refreshed.
## Citation
```bib
@article{10.1145/3512950,
author = {Liu, Dongyu and Alnegheimish, Sarah and Zytek, Alexandra and Veeramachaneni, Kalyan},
title = {MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series},
year = {2022},
issue_date = {April 2022},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {6},
number = {CSCW1},
url = {https://doi.org/10.1145/3512950},
doi = {10.1145/3512950},
journal = {Proc. ACM Hum.-Comput. Interact.},
month = {apr},
articleno = {103},
numpages = {30},
keywords = {anomaly detection, human-AI collaboration, collaborative analysis, visual analytics, time series, annotation}
}
```