The DS4C dataset is a structured collection of COVID-19 data from South Korea, based on reports from the Korea Centers for Disease Control & Prevention (KCDC) and local governments. It includes information on infections, patient routes, and various analyses. The dataset has been used for multiple research and visualization projects.
The Data Science for COVID-19 (DS4C) project provides a comprehensive dataset for analyzing the COVID-19 pandemic in South Korea. The dataset includes detailed information on infections, patient routes, and other relevant data. It has been used for various research and visualization projects, including competitions and academic studies. The data is sourced from the KCDC and local governments, ensuring accuracy and reliability.
The iBVP dataset is a collection of synchronized RGB and thermal infrared videos with PPG ground-truth signals acquired from an ear. It includes manual signal quality labels and dense signal-quality assessment using the SQA-PhysMD model. The dataset is designed to induce real-world variations in psycho-physiological states and head movement.
This study surveys the attitudes and behaviors of US higher education faculty members regarding online resources, the library, and related topics. It covers a wide range of issues, including faculty dependence on electronic scholarly resources, the transition from print to electronic journals, publishing preferences, e-books, and the preservation of scholarly journals.
PsychData is an online platform for hosting and conducting surveys and experiments in psychology, supporting secure data collection for researchers and students.