Heart rate (HR) and heart rate variability (HRV) are important vital signs for human physical and mental health. Recent research has demonstrated that photoplethysmography (PPG) sensors can infer HR and HRV. However, it is difficult to find a comprehensive PPG-based dataset for HR/HRV studies, especially for various study needs: multiple scenes, long-term monitoring, and multimodality (multiple PPG channels and extra acceleration data). In this study, we collected a comprehensive multimodal long-term dataset to address the gap of missing an all-in-one HR/HRV dataset (denoted as UTSA-PPG). We began by reviewing state-of-the-art datasets, emphasizing their strengths and limitations. Following this, we developed a custom data acquisition system and then collected the UTSA-PPG dataset and compared its key features with those of existing datasets. Additionally, five case studies were conducted, including comparisons with state-of-the-art datasets. The outcomes highlight the value of our dataset, demonstrating its utility for HR/HRV estimation exploration and its potential to aid researchers in creating generalized models for targeted research challenges.