Datasets:
Tasks:
Time Series Forecasting
Modalities:
Time-series
Languages:
English
Size:
1M<n<10M
ArXiv:
License:
File size: 2,010 Bytes
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license: cc-by-4.0
task_categories:
- time-series-forecasting
tags:
- time-series
- forecasting
- anomaly-detection
- classification
- TSLib
- tsfile
- modality:timeseries
- timeseries
- format:tsfile
pretty_name: MSL (TsFile)
size_categories:
- 1M<n<10M
configs:
- config_name: default
data_files:
- split: train
path: MSL_train.tsfile
- split: test
path: MSL_test.tsfile
- split: train_labels
path: labels/MSL_train_label.csv
- split: test_labels
path: labels/MSL_test_label.csv
modality:
- timeseries
- tabular
- text
language:
- en
---
# MSL (TsFile)
Apache TsFile version of the `MSL` anomaly-detection subset of
[`thuml/Time-Series-Library`](https://huggingface.co/datasets/thuml/Time-Series-Library).
## Overview
Mars Science Laboratory rover telemetry (55 channels) for anomaly detection.
- **Train:** 58,317 rows.
- **Test:** 73,729 rows.
- **Channels:** 55.
The train and test segments are stored as two separate TsFiles
(`MSL_train.tsfile` / `MSL_test.tsfile`), preserving the original split. Labels
are stored as separate CSV sidecar files in `labels/`.
## Schema (TsFile structure)
- **Time** (INT64, milliseconds) - row index * 1000 ms. The `.npy` source has no
timestamp, so this is a monotone 1 Hz proxy axis.
- **FIELD** (55 channels, FLOAT) - the sensor/metric channels.
- **Labels** (CSV sidecar) - `labels/MSL_train_label.csv` and
`labels/MSL_test_label.csv` contain `Time,label`. The train label file is all
0; the test label file carries the per-timestep anomaly labels.
No channels or rows are dropped. Labels are not stored inside the TsFile feature
tables.
## Usage
Read the `.tsfile` files with the Apache TsFile Java or Python SDK. Join labels
from the sidecar CSV files by `Time` within the matching split.
## Source & license
- Original dataset: https://huggingface.co/datasets/thuml/Time-Series-Library (subset `MSL`)
- Author / publisher: thuml (Tsinghua University)
- Paper: https://arxiv.org/abs/2407.13278
- License: CC BY 4.0
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