> For the complete documentation index, see [llms.txt](https://monitoring.toolkit.citiobs.eu/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://monitoring.toolkit.citiobs.eu/data-integration/how-to-add-visual-support-system.md). # How to add a data visualization to support decision? ## Description CitiObs Decision Support System (DSS) is a platform responsible for visualization of sensors observations on top of a map. Each sensor, which is an IoT device, can measure a variety of pollutants and meteorological conditions, as for example air temperature, relative humidity, ambient light, barometric pressure, noise level, particulate matter (PM1, PM2.5, PM10). Due to the large amount of data and their complexity DSS is an advanced integration tool that facilitates access to the data. DSS is developed in a friendly User Interface (UI), for easier and better navigation through the data. ## Why is this relevant? CitiObs Decision Support System (DSS) is a technological tool designed to enhance decision-making in the field of air pollution by visualizing sensor-based observations. Its use aims to increase awareness of air quality in specific areas of interest. The DSS provides users with an overview of air quality conditions in their chosen location, whether it is their residential area, a place where they are active, or a broader region. Additionally, it enables users to identify pollution trends over time, helping them take proactive measures to reduce exposure or advocate for environmental improvements. CitiObs DSS, gathers the data from Virtual Air, allowing to display data from different citizen science and citizen observatories initiatives, as all of them share the data using standard formats. ## How can this be done? Users of the platform can make informed decisions based on their selections and the observed values of each pollutant. They can choose a specific pollutant of interest and view sensor-based visualizations of its observations. For example, if a user selects air temperature, the system will display the latest readings from various sensors, with each observation color-coded to indicate its measured value at a specific location. Additionally, users can access a line graph representation of all recorded observations and download the data in multiple formats. By leveraging this information, users can adjust their actions and activities based on data-driven insights, gaining either a detailed or broad understanding of air pollution levels over the current or past periods. The data visualized in the DSS is managed, controlled, and enhanced by another component developed as part of the CitiObs Project. This component, called VirtualAir, acts as a central hub that integrates data from multiple sources. As an API, VirtualAir ensures that the information presented in the DSS is accurate and reliable, providing users with a clear and consistent view of air quality observations. ## Useful resources ... ## You might also be interested in * [How to centralize access to Analysis Ready Data?](/data-integration/how-centralize-access-ard.md) * [What to consider for increasing interoperability among sensor data infrastructures?](/data-platforms/what-to-consider-for-increasing-interoperability-among-sensor-data-infrastructures.md) --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://monitoring.toolkit.citiobs.eu/data-integration/how-to-add-visual-support-system.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.