Test Dataset

Context and methodology

This dataset was created as part of the "Urban Climate Resilience" research project, conducted at the Department of Environmental Sciences, University of Example. The project aims to study temperature and humidity variations in metropolitan areas to better understand the impacts of urban heat islands.

The dataset serves as the primary data source for the statistical analysis of microclimate conditions across three city districts, collected over the summer of 2024. Data was gathered using IoT-based environmental sensors deployed at 30 locations. Each sensor recorded temperature, humidity, and air pressure at 5-minute intervals.

Technical details

The dataset is organized into three main folders, one for each district ("District_A", "District_B", and "District_C"). Each folder contains daily CSV files named in the format YYYY-MM-DD_sensorID.csv. A README file at the root level explains the folder structure, file naming convention, and column definitions.

The CSV files can be opened with any standard spreadsheet software (e.g., Excel, LibreOffice) or programmatically using tools such as Python (pandas) or R. A Jupyter Notebook is included to demonstrate basic data loading and visualization.

Additional documentation and source code for the data collection scripts and analysis pipeline are available on the project's GitHub repository: https://github.com/example/urban-climate-resilience

Further details

Please note that while sensor calibration was performed prior to deployment, occasional anomalies may occur due to weather interference or battery fluctuations. Users are advised to apply the provided quality control script (quality_check.py) before analysis.

We encourage reuse and welcome collaboration. If you use this dataset in your work, please cite it using the provided DOI.