computer science

Observations and Measurements

Observations and Measurements is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Observations and Measurements rather than just read about it. In short: 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 geospatial information.

Key takeaways

Observations and Measurements belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Observations and Measurements to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Observations and Measurements from memory before moving on to harder problems.

Reference excerpt

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 geospatial information. O&M is one of the core standards in the OGC Sensor Web Enablement suite, providing the response model for 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, 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). 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.

Sampling features The standard also provides a schema for Sampling Features. Observations commonly involve sampling of the ultimate feature of interest. Specific sampling features, such as station, specimen, transect, section, are used in many application domains, and common processing and visualization tools are used. The standard defines a common set of sampling feature types classified primarily by spatial dimension, as well as samples for ex situ observations. The schema includes relationships between sampling features (sub-sampling, derived samples). The core properties of sampling features are:

sampled feature – which links the sampling artefact with the real-world feature of interest related observation related sampling feature – linking sampling features into complexes

Implementations An XML encoding (GML Application Schema) is provided for transfer of data:

Observation schema (XSD) Sampling features (XSD) A JSON encoding is provided for transfer of data:

JSON Schema An explicit OWL representation of O&M is available:

Observation schema (OWL2) Archived 2015-10-07 at the Wayback Machine Sampling features (OWL2) Archived 2015-10-07 at the Wayback Machine. The W3C Semantic Sensor Network Ontology provides an updated OWL implementation that covers most of O&M . Version 2.0 of the Observations Data Model ("ODM2"), developed by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) and the Critical Zone Observatory project, adapts O&M.

ODM2 model and software

Related documents O&M is also published as a topic of the Open Geospatial Consortium Abstract Specification. The previous version of O&M (Version 1) factored the model into two documents: Part 1 described the Observation Schema, and Part 2 described Sampling Features.

See also Observation Semantic Sensor Web SensorML

External links Observations and Sampling Archived 2008-07-23 at the Wayback Machine Wiki page @ SEEGrid with examples from environmental sciences (no login required)

References

Worked examples

Example 1 — a first encounter with Observations and Measurements

Start with the simplest possible case. Write down what Observations and Measurements claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Observations and Measurements before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Observations and Measurements ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Observations and Measurements

In research: Observations and Measurements appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Observations and Measurements in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Observations and Measurements is common in secondary-school and first-year university syllabi. It links to neighbouring topics Geographic data and information, ISO/TC 211, ISO standards, so understanding it makes those chapters shorter.
In everyday life: Look for Observations and Measurements outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Observations and Measurements” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Observations and Measurements in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Observations and Measurements means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Observations and Measurements out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Observations and Measurements in simple terms?

Why does Observations and Measurements matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Observations and Measurements?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Observations and Measurements.