The archive contains many interesting datasets, including a gesture dataset featuring the same two actors, but recorded 16 years apart! (we are nothing if not patient!). The datasets are mostly designed for testing classification and clustering algorithms, but we are sure that the creative community will find other uses for it. The archive is accompanied by a paper. Beyond explaining this resource, this paper offers pragmatic advice to anyone who may wish to evaluate a new algorithm on the archive. In addition, the paper makes a novel and actionable claim: of the hundreds of papers that show an improvement over the standard baseline (1-Nearest Neighbor classification), a large fraction may be misattributing the reasons for their improvement).

Please reference as: Hoang Anh Dau, Eamonn Keogh, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi , Chotirat Ann Ratanamahatana, Yanping Chen, Bing Hu, Nurjahan Begum, Anthony Bagnall , Abdullah Mueen and Gustavo Batista (2018). The UCR Time Series Classification Archive. URL https://www.cs.ucr.edu/~eamonn/time_series_data_2018/

Ref: @misc{UCRArchive2018, title = {The UCR Time Series Classification Archive}, author = {Dau, Hoang Anh and Keogh, Eamonn and Kamgar, Kaveh and Yeh, Chin-Chia Michael and Zhu, Yan and Gharghabi, Shaghayegh and Ratanamahatana, Chotirat Ann and Yanping and Hu, Bing and Begum, Nurjahan and Bagnall, Anthony and Mueen, Abdullah and Batista, Gustavo}, year = {2018}, month = {October}, note = {\url{https://www.cs.ucr.edu/~eamonn/time_series_data_2018/}} }