- Sachit Mahajan: Computational Social Science, Department of Humanities, Social and Political Sciences, ETH Zürich, 8092 Zürich, Switzerland. ORCID
Recent advances in sensor technology and the availability of low-cost and low-power sensors have changed the air quality monitoring paradigm. These sensors are being widely used by scientists and citizens for monitoring air quality at finer spatial-temporal resolution. Such practices are opening up opportunities to enhance the traditional monitoring networks, but at the same time, these sensors are producing large data sets that can become overwhelming and challenging when it comes to the scientific tools and skills required to analyze the data. To address this challenge, an open-source, robust, and cross-platform sensor data analysis toolbox called is developed that allows researchers and citizens to do detailed and reproducible analyses of air quality data. combines the power of visualization and statistical analysis using a simple and intuitive graphical user interface. Additionally, it offers a comprehensive set of tools for systematic analysis such as data conversion, interpolation, aggregation, and prediction. Even though was developed with air quality research in mind, it can be used to analyze different kinds of time-series data.