The Total Errors Sheet for Datasets (TES-D) is a template-based approach for documenting datasets from online sources such as social media or Wikipedia, focusing on potential errors throughout the research process. It provides a structured catalogue of questions to guide researchers in reflecting critically on data collection and potential measurement or representation errors. Completed TES-D documentation is intended to accompany the dataset, enhancing transparency, reproducibility, and responsible reuse, as illustrated by the “Call me sexist, but…” dataset by Samory et al. (2021), where structured documentation enhances interpretability and reuse.

Further information: This tool was developed as part of the KODAQS project, a partnership between GESIS, the University of Mannheim, and LMU Munich.