A virtual sensor system for user-generated, real-time environmental data products

With the advent of new instrumentation and sensors, more diverse types and increasing amounts of data are becoming available to environmental researchers and practitioners. However, accessing and integrating these data into forms usable for environmental analysis and modeling can be highly time-consuming and challenging, particularly in real time. For example, radar-rainfall data are a valuable resource for hydrologic modeling because of their high resolution and pervasive coverage. However, radar-rainfall data from the Next Generation Radar (NEXRAD) system continue to be underutilized outside of the operational environment because of limitations in access and availability of research-quality data products, especially in real time. This paper addresses these issues through the development of a prototype Web-based virtual sensor system at NCSA that creates real-time customized data streams from raw sensor data. These data streams are supported by metadata, including provenance information. The system uses workflow composition and publishing tools to facilitate creation and publication (as Web services) of user-created virtual sensors. To demonstrate the system, two case studies are presented. In the first case study, a network of point-based virtual precipitation sensors is deployed to analyze the relationship between radar-rainfall measurements, and in the second case study, a network of polygon-based virtual precipitation sensors is deployed to be used as input to urban flooding models. These case studies illustrate how, with the addition of some application-specific information, this general-purpose system can be utilized to provide customized real-time access to significant data resources such as the NEXRAD system. Additionally, the creation of new types of virtual sensors is discussed, using the example of virtual temperature sensors.

► We develop a Web-based system for creating customized environmental data streams.
► Our system encourages collaboration and helps democratize data product creation.
► Case studies explore the production of radar-rainfall virtual sensors.
► Our system is generic to many different types of real-time environmental data.