Supplementary Data for: Bridging the Cognitive Gap in Task Mining: Identifying Physiological Metrics for Cognitive Load Estimation in Office Work Environments

This repository contains the supplementary dataset associated with the research paper titled "Bridging the Cognitive Gap in Task Mining: Identifying Physiological Metrics for Cognitive Load Estimation in Office Work Environments". The dataset provides a comprehensive, structured catalog of physiological metrics used for Cognitive Load (CL) estimation, extracted from a tertiary study of 83 scientific documents. This structured catalog lays the groundwork for developing inferential models that integrate physiological data streams with discrete Task Mining event logs. Dataset Contents and File Structure: The provided Excel file (.xlsx) consolidates the data for the 183 physiological metrics corresponding to 11 different categories identified in the literature review. This dataset is the primary source used to generate the figures and the detailed tables presented in Appendix A of the original manuscript. The file contains the following key variables and metadata: Metric ID: A unique identifier assigned to each extracted physiological metric (e.g., "EYE01"). Physiological Metric: The specific name of the physiological metric as reported in the literature (e.g., "Pupil Diameter (PD)"). Category: The physiological grouping of the physiological metric (e.g., "Eye Tracking") Subcategory: The physiological subgrouping of the physiological metric (e.g., "Pupillometry"). Sources: The specific primary studies or documents from the literature review that mention and/or utilize the physiological metric. Publication Year of Sources: The specific publication year for each referenced source. CL Relevance: A three-level label assigned to each metric indicating the strength of empirical evidence supporting its association with Cognitive Load. Publication Year Median: The median publication year of the sources associated with a specific metric. Mean Value of Sources per Metric: The average number of sources citing the metrics within a specific physiological category. Median Year of Sources (Category Level): The median publication year of all sources within a specific physiological category. Context and Usage: Researchers and practitioners can use this dataset to identify the most viable and empirically supported physiological indicators of CL. The data allows for the reproducibility of the tables (Appendix A) and graphs featured in the paper, and serves as a foundational baseline for future human-centered automation studies.