This upload contains the dataset from the paper "Cookiescanner: An Automated Tool for Detecting and Evaluating GDPR Consent Notices on Websites" presented at ARES 2023. Folder Structure - 01_bert_classifier: The final BERT model as well as the datasets and Jupyter notebook to train/evaluate it. Additionally, the folder also contains a small flask application and a Docker file to deploy it as a web service. - 02_raw_dataset: The 1.000 sampled scans. The results.json contains the raw scan data, while the rest of the subfolders contain the screenshots of the detection methods. - 03_banner_detection: Contains the analysis CSV file, as well as a folder with the banner screenshots. - 04_dark_patterns: Analysis files as well as the screenshots of banners with the dark patterns from the paper. Source Code For the source code of the scanner, please refer to https://github.com/UBA-PSI/cookiescanner.