Schaaf, Hylke van derHylke van derSchaafMoßgraber, JürgenJürgenMoßgraberGrellet, S.S.GrelletBeaufils, M.M.BeaufilsSchleidt, K.K.SchleidtUsländer, ThomasThomasUsländer2022-03-142022-03-142020https://publica.fraunhofer.de/handle/publica/40799910.1007/978-3-030-39815-6_22In many application domains sensor data contributes an important part to the situation awareness required for decision making. Examples range from environmental and climate change situations to industrial production processes. All these fields need to aggregate and fuse many data sources, the semantics of the data needs to be understood and the results must be presented to the decision makers in an accessible way. This process is already defined as the ""sensor to decision chain"" [11] but which solutions and technologies can be proposed for implementing it? Since the Internet of Things (IoT) is rapidly growing with an estimated number of 30 billion sensors in 2020, it offers excellent potential to collect time-series data for improving situational awareness. The IoT brings several challenges: caused by a splintered sensor manufacturer landscape, data comes in various structures, incompatible protocols and unclear semantics. To tackle these challenges a well-defined interface, from where uniform data can be queried, is necessary. The Open Geospatial Consortium (OGC) has recognized this demand and developed the SensorThings API (STA) standard, an open, unified way to interconnect devices throughout the IoT. Since its introduction in 2016, it has shown to be a versatile and easy to use standard for exchanging and managing sensor data. This paper proposes the STA as the central part for implementing the sensor to decision chain. Furthermore, it describes several projects that successfully implemented the architecture and identifies open issues with the SensorThings API that, if solved, would further improve the usability of the API.en004670An Environmental Sensor Data Suite Using the OGC SensorThings APIconference paper