This website is an ongoing project to develop a comprehensive repository for research into time series classification. If you use the results or code, please cite the paper "Anthony Bagnall, Jason Lines, Aaron Bostrom, James Large and Eamonn Keogh, The Great Time Series Classification Bake Off: a Review and Experimental Evaluation of Recent Algorithmic Advances, Data Mining and Knowledge Discovery, 31(3), 2017". Paper Link, Bibtex Link. We are in the process of updating all the results for the new datasets.
If you want to just reference the website, please do so as: "Anthony Bagnall, Jason Lines, William Vickers and Eamonn Keogh, The UEA & UCR Time Series Classification Repository, www.timeseriesclassification.com".
If you want to donate data, have any queries or problems with any of the datasets or want to give feedback on the website, please raise an issue on the associated Github repo.
There are two code repositories associated with this website. The Java based, weka compatible toolkit tsml and the python based, sklearn compatible sktime.
The univariate TSC archive was relaunched in 2018 with 128 datasets.
Weka formatted ARFF files (and .txt files) (about 500 MB).
sktime formatted ts files (about 250 MB).
more info The univariate TSC archive can be referenced with this paper.
Weka formatted ARFF files (and .txt files) (about 2 GB).
sktime formatted ts files (about 1.5 GB).
more info. The archive can be referenced with this paper.