5.3.1 SWE common

From Geostandards

Contents 1 Overview 1.1 Simple Data Types 1.2 Aggregate Data Types 1.3 Position Data 1.4 Temporal Aggregates 1.5 Encoding 1.6 Phenomenon

Overview

SweCommon defines several basic value types and data encodings that will exist in the SWE Common namespace. These include definitions that are expected to be shared among different parts of the SWE framework, including SWE encodings and services. SweCommon lays down the basis for the information model and is used in the service model, too.

In the 1.0 version of the SWE specifications, SweCommon is part of the SensorML specification. But in future versions, the SWE common components will be defined in a separate standard.

SWE Common specifies a set of data types and related components. These can be classified into the following categories:

• primitive data types complementing the GML types
• aggregate data types like records, array, vectors and matrices
• specialized data types for expressing positions, curves or time-aggregates
• encodings for quality indications or semantic annotations

The next subsections will introduce the different elements of SWE Common more detailed.

Simple Data Types

The simple data types within SWE Common can be seen as basic elements for creating more complex data types. In order to provide the necessary means for expressing such basic data types, SWE Common offers encodings for the following elements:

• boolean values: true or false
• categories: textual data that is contained in a certain vocabulary of allowed values
• text
• numerical data types: values in form of numbers that are accompanied by a unit of measurement
• quantities and quantity ranges
• counts
• time and time spans

Aggregate Data Types

The basic data types described in the previous subsection can be grouped into so called aggregate data types. Within SWE Common two groups of such aggregate data types are defined:

• generic aggregates
• specialized aggregates

Generic aggregates provide means for constructing complex data types. They include

• data records: collections of data values of any type (the concept of a data record is based on the Composite Design Pattern)
• simple data records: data records which are restricted to scalar values
• data arrays: collections of any data values that contain a specified number of elements

Opposed to this, specialized aggregates are intended for specific purposed. SWE Common comprises the following specialized aggregates:

• conditional values: specific kind of a record in which the values are dependent one or more conditions
• curves: a type of array that links a ordered set of coordinate values to an independent coordinate axis
• normalized curves

Position Data

For expressing the spatial relationships of sensors and their measured data, specific needs arise with regard to the description of positions. Especially parameters that go beyond the pure location are often of interest. These include information like velocity, orientation and acceleration. The following position types are available in SWE Common:

• positions
• envelopes
• vectors
• square matrices

Temporal Aggregates

The temporal aggregates within SWE Common offer a complementary set of the basic temporal elements defined by ISO 19108. These include temporal grids, temporal instant grids and temporal interval grids.

Encoding

There are cases in which sensor data can be better encoded by using other means than XML based formats. In order to support such encodings, SWE Common provides means for describing these encodings so that it becomes possible to decode them. The following encodings are supported:

• text block: in this case the sensor data is ASCII encoded; for decoding it, information like the separators between text blocks or tokens have to be described
• binary block: here the data is encoded in a binary format which can be described within this element
• standard format: this allows to refer to well known standard encodings of data (e.g. jpeg or gif)

Phenomenon

Using SWE Common the phenomena observed by a sensor can be described. This is especially important for providing information about the semantics of certain values. Basically the following three classes of phenomena are offered:

• phenomenon: this is the basic type of a phenomenon which contains mainly its identifier
• constrained phenomenon: in this case certain restrictions to the phenomenon can be defined; for example the medium to which a measured value is related can be specified
• composite phenomena: here, several phenomena can be combined to a bigger more complex one (e.g. wind is a complex phenomenon composed of wind speed and wind direction)

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