The Algorithmic Information Theory (AIT) Data Compression Challenge consists of building a lossless compression system with both a compressor and a decompressor. The implementation must stay within 8 GB of peak RAM, and the decompressor binary must not exceed 1024 KB. Participants were strongly encouraged to use arithmetic coding. Submissions had to follow the formats CompressorName inputFileName outputFileName and DecompressorName inputFileName outputFileName, and be sent to pratas@ua.pt. The competition data was divided into two parts: a Training dataset and a Testing dataset. The Training dataset was visible to competitors throughout the competition, and intermediate results on that portion were regularly updated and made available. The Testing dataset, by contrast, was kept hidden until the end of the competition. Final evaluation on the Testing dataset was performed using the compressors optimized by participants on the Training data. The Testing portion represents approximately two thirds of the full dataset. Results can be viewed per dataset and also as an overall aggregate across all files. Times are calculated using the median. The Weissman score is computed against gzip for the currently selected dataset. To download the dataset, click here. In the Ranking Table, click the column headers to sort. Search and Ignore can be used with text patterns, and these filters can be combined.