: Public abstract Class
Created: 25/11/2009 15:36:33
Modified: 25/11/2009 16:41:42
Project:
Advanced:
Attribute
Public Percentage
  accuracy

Details:
attribute=yes
changed=new
definition=The extent to which the value is expected to be free from error, measured as a percentage of the data value. 100% means fully accurate.
order=2
origin=DATEX
originalCode=ACU
originalName=Accuracy
type=content
 
Public ComputationMethodEnum
  computationalMethod

Details:
attribute=yes
changed=yes
definition=Method of computation which has been used to compute this data value.
order=3
origin=DATEX
originalCode=COM
originalName=Computation method
type=content
 
Public Boolean
  dataError

Details:
changed=new
definition=Indication of whether the value is deemed to be erroneous by the supplier, (true = erroneous). If not present the data value is assumed to be ok. This may be used when automatic fault detection information relating to sensors is available.
order=0
origin=- null -
originalCode=- null -
originalName=- null -
type=content
 
Public NonNegativeInteger
  numberOfIncompleteInputs

Details:
attribute=yes
changed=new
definition=The number of inputs detected but not completed during the sampling or measurement period; e.g. vehicles detected entering but not exiting the detection zone.
order=4
origin=- null -
originalCode=- null -
originalName=- null -
type=content
 
Public NonNegativeInteger
  numberOfInputValuesUsed

Details:
attribute=yes
changed=new
definition=The number of input values used in the sampling or measurment period to determine the data value.
order=5
origin=- null -
originalCode=- null -
originalName=- null -
type=content
 
Public MultilingualString
  reasonForDataError

Details:
changed=new
definition=The reason why the value is deemed to be erroneous by the supplier.
order=1
origin=- null -
originalCode=- null -
originalName=- null -
type=content
 
Public Float
  smoothingFactor

Details:
attribute=yes
changed=new
definition=Coefficient required when a moving average is computed to give specific weights to the former average and the new data. A typical formula is, F being the smoothing factor: New average = (old average) F + (new data) (1 - F).
order=6
origin=DATEX
originalCode=SMF
originalName=Smoothing factor
type=content
 
Public Float
  standardDeviation

Details:
attribute=yes
changed=new
definition=The standard deviation of the sample of input values from which this value was derived, measured in the units of the data value.
order=7
origin=- null -
originalCode=- null -
originalName=- null -
type=content
 
Public Percentage
  supplierCalculatedDataQuality

Details:
attribute=yes
changed=new
definition=A measure of data quality assigned to the value by the supplier. 100% equates to ideal/perfect quality. The method of calculation is supplier specific and needs to be agreed between supplier and client.
order=8
origin=- null -
originalCode=- null -
originalName=- null -
type=content
 
Tag Value
changed new
Details:
 
definition A data value of something that can be measured or calculated. Any provided meta-data values specified in the attributes override any specified generic characteristics such as defined for a specific measurement in the MeasurementSiteTable.
Details:
 
origin - null -
Details:
 
originalCode - null -
Details:
 
originalName - null -
Details:
 
type content
Details:
 
Object Type Connection Notes
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ConcentrationOfVehiclesValue Class Generalization  
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DirectionBearingValue Class Generalization  
DirectionCompassValue Class Generalization  
DurationValue Class Generalization  
FloatingPointMetreDistanceValue Class Generalization  
IntegerMetreDistanceValue Class Generalization  
KilogramsConcentrationValue Class Generalization  
MicrogramsConcentrationValue Class Generalization  
PercentageValue Class Generalization  
PrecipitationIntensityValue Class Generalization  
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TrafficStatusValue Class Generalization  
PcuFlowValue Class Generalization  
VehicleFlowValue Class Generalization  
OccupancyChangeValue Class Generalization  
VehicleCountValue Class Generalization