## 3 New Generation Sensor Web Enablement
### Evolvement of SWE Information Model
#### 3.2.2 Description of Measured Sensor Data  
The Observations & Measurements standard defines a domain independent, conceptual model for the representation of (spatiotemporal) measurement data. It comprises an implementation of this conceptual model as an XML based GML application schema. ISO defines an _application schema_ as a conceptual schema for data required by one or more applications. Thus, O&M can be seen as a conceptual schema for sensor applications based upon GML. O&M is particularly used for the creation of response documents for the _GetObservation_ operation of the SOS (Section 3.3.2). However, O&M can also be used as a generic means to deal with measurements in a standardized way. The above has been the case for the first version of O&M [53, 54] and is also the case for O&M 2.0. However, conceptual model and its encoding are now more strictly divided. In fact, the major objective of the development of O&M 2.0 has been to harmonize it with existing foundational ISO models and to bring it into the ISO standardization process. This aim has been achieved, and the conceptual model of O&M 2.0 has reached the status of an ISO final draft international standard [60] while its XML implementation is integrated into the more technical standards landscape of the OGC [61]. The basic observation model as designed in O&M 2.0 is shown in Figure 3. An _observation_ has a relationship to a _procedure_ representing the process which has performed the observation, e.g., a physical sensor or a simulation. The _observed property_ points to a description of the property which is observed (e.g., \"water temperature\" or \"salinity\"). The observation's _result_ is not restricted to a certain type in the basic observation model and can be of any type, ranging from a single measurement to an n-dimensional coverage of values. Subtypes of the basic observation then restrict the type of the result. The _feature of interest_, the computational representation of a real world feature (e.g., \"Gulf of Mexico\" or \"water gauge X at Mississippi river\") carries the property which is observed. The observation provides a value for this property at a certain time, the _phenomenon time_. The phenomenon time was formerly called sampling time and was renamed to better reflect that it represents the time when the observation's result applies to the observed property. In addition to the phenomenon time, an observation contains two other temporal properties: _result time_ and _valid time_. The mandatory result time property represents the time when the observation's result was produced. The valid time is an optional property introduced in O&M 2.0 that defines the time period for which the observation's result is usable. This is for example valuable in forecasting scenarios where a weather forecast made at 9:00 may already be superseded by a new forecast made at 10:00--the valid time of the first forecast would then be the time period that starts at 9:00 and ends at 10:00. Spatial information for an observation is usually given by a location property of the feature of interest. However, in O&M 2.0, a new spatial profile facilitates the provisioning of an observation's sampling geometry--the spatial extent that the result of the observation applies to. This is usually the extent of the observation's feature of interest. Without the profile, this information has to be extracted from the feature of interest, which could involve complex computations of the actual geometry and can also require dealing with previously unknown feature types. Also newly introduced in O&M 2.0 is the _related observation_ property. This property can be used to express relationships between observations. Coming back to the weather forecasting scenario, this property can be utilized to model a \"supersede\" relationship between two successively computed forecasting observations. Removed from the O&M data model is the data type that served as a  
Figure 3: Basic observation model of O&M 2.0.  
container for collections of observations.