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Observations and Measurements (O&M) is an International Standard which defines a conceptual schema encoding for observations, and for features involved in sampling when making observations. While the O&M standard was developed in the context of geographic information systems, the model is derived from generic patterns proposed by Fowler and Odell,〔 〕 and is not limited to spatial information. O&M is one of the core standards in the OGC Sensor Web Enablement suite, providing the response model for Sensor Observation Service〔(【引用サイトリンク】title=OGC Standard – Sensor Observation Service )〕 (SOS). ==Observation schema== The core of the standard provides the observation schema. An ''observation'' is an act that results in the estimation of the value of a feature property, and involves application of a specified procedure, such as a sensor, instrument, algorithm or process chain. The procedure may be applied in-situ, remotely, or ex-situ with respect to the sampling location. Use of a common model for observation metadata allows data to be combined unambiguously, across discipline boundaries. Observation details are also important for data discovery and for data quality estimation. An observation is defined in terms of the set of properties that support these applications. O&M defines a core set of properties for an observation: * feature of interest * observed property * result * procedure – the instrument, algorithm or process used (which may be described using SensorML) * phenomenon time – the real-world time associated with the result * result time – the time when the result was generated * valid time – the period during which the result may be used The key to the model is the division of the observation and its feature of interest, separating the concerns so that the appropriate information associated with the description of each object. This allows a unified treatment of ''in situ'', ''ex-situ'', and remote-sensed observations. The observation schema may also be understood as a corollary of the General Feature Model from ISO 19101,〔(【引用サイトリンク】year=2002 )〕 providing metadata associated with the estimation of the value of a feature property. The Observation model takes a user-centric viewpoint, emphasizing the semantics of the feature-of-interest and its properties. This contrasts with sensor oriented models such as SensorML, which take a process – and thus provider-centric viewpoint. Many observations are made to detect the variation of some property in the natural environment, expressed as a spatial function or ''field'', also known as a ''coverage'' (ISO 19123:2005〔(【引用サイトリンク】year=2005 )〕). The relationship between observations, features and coverages is explained, in the context of ocean observations and modeling, in a report for GEOSS Architecture Implementation Pilot 3. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Observations and Measurements」の詳細全文を読む スポンサード リンク
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