‐ r
The root of the dictionary is located at http:dictionary.uncertml.org and follows a pseudo‐ RESTful design pattern. All statistics are located at statistics with the name of the statistic
following ‐ e.g. the definition of the statistic mean would be located at the following URL: http:dictionary.uncertml.orgstatisticsmean. f the specified statistic has any parameters,
these can be found at: http:dictionary.uncertml.orgstatisticsstatistic nameparameters. ndividual parameter information can be located at the following:
http:dictionary.uncertml.orgstatisticsstatistic nameparametersparameter name. The same structure is applied to all parametric distributions, with the word distributions
substituted for statistics .
An XSLT stylesheet exists to allow a human‐readable view of the entire dictionary and allows easy navigation through the various statistics and distributions.
6.1.2 Parameter
The second base type in UncertML is the Parameter,
this type is common to all parametric distributions and certain statistics.
Figure 5: The Parameter type distributions and certain statistics.
Displayed in Figure , the Parameter
type contains two properties: definition
and value
. The
definition of a
Parameter is identical to that of the
AbstractUncertaintyType and references a dictionary definition of a particular statistic or distribution parameter. The
value of a
Parameter contains any simple XML type, typically an integer or double value.
is common to
6.2 Realisations
n some situations, a user may not be able to simply represent the uncertainties of the data they are working with. n such a situation, a sample from the random quantity might be provided,
allowing uncertainty to be described implicitly. owever, when using this approach, a sufficiently large sample is required to deduce the uncertainties inherent in the data, which
means that efficient encapsulation of large data volumes is an important issue for UncertML. The following sections discuss the
Realisations type available within UncertML for
describing a sample of data through a series of realisations.
‐ r
f a Realisations type in UncertML .
Extending the AbstractUncertainty
type discussed in Section . . provides a definition
property. n this instance the UR, if required, should resolve to a definition of the concept of a realisation. Two optional properties are included to provide greater information
about any particular set of realisations. The realisedFrom
property is a UR that links to a definition of the distribution from which the realisations are generated, where this can be
provided. The second property, samplingMethod
, is a UR resolving to the definition of the particular method that was used to sample the realisations. The
realisationCount contains
the number of realisations in each sample; this information is useful when describing multiple random quantities at multiple domain points. Domain point here refers to a unique sampling
location in a simulation series, which will often, but not always, be distinguished by its location
Figure 6: Structure o
in space andor time. As with all other array types in UncertML, the
Realisations type is based around the SWE
Common DataArray
type . owever, as the Realisations
type can only describe a series of realisations, the
elementType property of the
DataArray is not used. The
elementCount property is used to indicate the total number of values contained within the
array. n cases where a dataset describes a single variable at a single domain point, this value will be the same as the
realisationsCount property. When describing multiple variables
andor or multiple domain points, the size of the elementCount
will be the product of the number of variables, number of domain points and the number of individual realisations. More
information about how to decode the information within the array may be found in Section . The last two properties are directly inherited from the SWE Common encoding schema, which
provides an efficient and flexible solution to encoding data arrays. Loosely speaking, the format of the data binary, ASC, XML etc is described in the
encoding property and the
values property contains the data which relates to the
elementType ; i.e. the actual values realised
through sampling. More information about the SWE Common encoding schema can be found in and example encodings are detailed in Section .
Aggregate types within UncertML, whether they be arrays or records, do not extend the AbstractUncertainty
type, as they are merely perceived as containers for uncertainty types with each individual constituent containing its own definition.
6.3 Statistics
