Sensor systems have the potential to make abstract science phenomena concrete for K-12 students. Internet of Things (IoT) sensor systems provide a variety of benefits for modern classrooms, creating the opportunity for global data production, orienting learners to the opportunities and drawbacks of distributed sensor and control systems, and reducing classroom hardware burden by allowing many students to "listen" to the same data stream. To date, few robust IoT classroom systems have emerged, partially due to lack of appropriate curriculum and student-accessible interfaces, and partially due to lack of classroom-compliant server technology. In this article, we present an architecture and sensor kit system that addresses issues of sensor ubiquity, acquisition clarity, data transparency, reliability, and security. The system has a dataflow programming interface to support both science practices and computational data practices, exposing the movement of data through programs and data files. The IoT Dataflow System supports authentic uses of computational tools for data production through this distributed cloud-based system, overcoming a variety of implementation challenges specific to making programs run for arbitrary duration on a variety of sensors. In practice, this system provides a number of unique yet unexplored educational opportunities. Early results show promise for Dataflow as a valuable learning technology from research conducted in a high school classroom.