Observation - opengeospatial/Geotech GitHub Wiki
What is an Observation?
An observation is an act associated with a discrete time instant or period through which a number, term or other symbol is assigned to a characteristic. This act 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. The result of an observation is an estimate of the value of a property of some feature; an observation is a property-value-provider for a feature-of-interest. Use of a common model allows observation data using different procedures to be combined unambiguously.
In conventional measurement theory the term “measurement” is used. However, a distinction between measurement and category-observation has been adopted in more recent work so the term “observation” is used here for the general concept. “Measurement” may be reserved for cases where the result is a numerical quantity.
The observation itself is also a feature, since it has properties and identity. Observation details are important for data discovery and for data quality estimation. The observation could be considered to carry “property-level” instance metadata, which complements the dataset-level and feature-level metadata commonly provided via catalogue services (e.g. ISO 19115 or other community agreed one).
Realizations
| Data model | Concept name | Definition |
|---|---|---|
| OGC OMS | Observation | An observation is an act associated with a discrete time instant or period through which a number, term or other symbol is assigned to a characteristic. This act 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. The result of an observation is an estimate of the value of a property of some feature; an observation is a property-value-provider for a feature-of-interest. Use of a common model allows observation data using different procedures to be combined unambiguously. |
| IFC | GeoscienceObservation | Detailed collected information, including measured parameters, descriptions etc. related to geoscientific observations that can be assigned to physical or spatial elements using IfcRelAssignsToProduct. |
| AGS | No specific concept as such as all data is treated similarly in AGS data, whether it be location data, hole/test/other metadata or results (i.e. observations in this context) | |
| DIGGS | Observation | An interval or region defined at a sampling feature that contains qualitative observations or interpretations. |
| DIGGS | Measurement | An act or event whose results are quantitative estimates of the values of properties of the target of an investigation. DIGGS currently has three specialized measurement objects, 1) a Test, which is a measurement made over a spatial domain, such as laboratory tests on samples collected in the field, or in-situ tests where measurements are made directly on site, 2) monitoring activities, which are measurements made over a temporal domain, such as water level measurements or inclinometer readings, and 3) a Material Test, which is for measurements made on material samples that are manufactured such that the result pertains only to the sample and not to any associated location. |
FAQ
Observations and / or measurements?
Several distinctions can be made between Observations and Measurements. A common one being that Observations provide qualitative results whereas Measurements provide quantitative results.
The proposed conceptual model does not make this distinction. Yet soft typing can be applied if this distinction is considered necessary.
The DIGGS standard proposes an explicit distinction between Observations and Measurements.
How to deal with multiple Observations / measurements?
It is very common for a procedures or test (especially for measurements) to provide a result composed of multiple values. This includes time series, z-series.
The proposed conceptual model offers a fine granularity which aims at being able to get any value separately. Each single observation or measurement (eg. at a specific time of a timeseries and/or at a specific location of a z-series) is then contextualized and associated to its procedure and other metadata.
I don't want to retrieve single observations / measurements but have them grouped
Grouping of observations and measurements having some similarities is a basic function that Observation APIs shall be able to manage.
Common grouping criteria include: ObservingProcedure, ObservedProperty, Time, Location and/or FeatureOfInterest.
OGC APIs like SensorThingAPI offer such capacity.