OPC 10000-4 specifies all Services needed for OPC UA Aggregates. In particular:

  • The Browse Service Set or Query Service Set to detect Aggregates and their configuration.
  • The HistoryRead Service of the Attribute Service Set to read the aggregated history of the HistoricalNodes.
  • The CreateMonitoredItems Service allows specifying a filter for each MonitoredItem to read aggregated data.

The HistoryRead service defined in OPC 10000-4 can perform several different functions. The historyReadDetails parameter is an Extensible Parameter that specifies which function to perform. The ReadProcessedDetails structure is used to read aggregated data for HistoricalDataNodes.

The CreateMonitoredItems Service allows specifying a filter for each MonitoredItem. The MonitoringFilter is an extensible parameter whose structure depends on the type of item being monitored. The AggregateFilter structure is used to obtain aggregated data for a subscription.

ReadProcessedDetails structure is formally detailed in OPC 10000-11. Table 6 outlines the components of the ReadProcessedDetails structure for the purposes of discussion in this document.

Table 6 – ReadProcessedDetails

Name

Description

ReadProcessedDetails

Specifies the details used to perform a “processed” history read.

startTime

Beginning of period to read.

endTime

End of period to read.

processingInterval

Interval between returned Aggregate values.

aggregateType[]

The NodeIds of the AggregateFunction Objects. AggregateFunction Objects indicate the list of Aggregates to be used when retrieving processed history.

aggregateConfiguration

Aggregate configuration structure.

useServerDefaults

If True the Server’s default values are used and any values specified for the other parameters are ignored.

treatUncertainAsBad

See 4.2.1.2.

percentDataBad

See 4.2.1.2.

percentDataGood

See 4.2.1.2.

useSlopedExtrapolation

See 4.2.1.2.

The AggregateFilter defines the Aggregate function that should be used to calculate the values to be returned. The AggregateFilte r is formally defined in OPC 10000-4. Table 7 outlines the components of the AggregateFilter structure for the purposes of discussion in this document.

Table 7 – AggregateFilter structure

Name

Description

AggregateFilter

startTime

Beginning of period to calculate the Aggregate the first time.

aggregateType

The NodeIds of the AggregateFunction Objects that indicates the list of Aggregates to be used when retrieving processed data.

processingInterval

The period to be used to compute the Aggregate.

aggregateConfiguration

This parameter allows Clients to override the Aggregate configuration settings supplied by an AggregateConfiguration Object on a per monitored item basis.

useServerDefaults

If True the Server’s default values are used and any values specified for the other parameters are ignored.

treatUncertainAsBad

See 4.2.1.2.

percentDataBad

See 4.2.1.2.

percentDataGood

See 4.2.1.2.

useSlopedExtrapolation

See 4.2.1.2.

Subclause 5.3 defines additional codes and rules that apply to the StatusCode when used for Aggregates.

The general structure of the StatusCode is specified in OPC 10000-4. It includes a set of common operational result codes which also apply to Aggregates.

In OPC UA Aggregates the StatusCode is used to indicate the conditions under which a value or Event was stored, and thereby can be used as an indicator of its usability. Due to the nature of aggregated data, additional information beyond the basic quality and call result code needs to be conveyed to the client. For example, whether or not the result was Interpolated, were all data inputs to a calculation of Good quality, etc.

In the following, Table 8 contains codes with Bad severity indicating a failure; Table 9 contains codes with Uncertain severity indicating that the value has been retrieved under sub-normal conditions. It is important to note, that these are the codes that are specific for OPC UA Aggregates and that they supplement the codes that apply to all types of data; they are therefore defined in OPC 10000-4, OPC 10000-8 and OPC 10000-11.

Table 8 – Bad operation level result codes

Symbolic Id

Description

Bad_AggregateListMismatch

The requested number of Aggregates does not match the requested number of NodeIds. When multiple Aggregates are requested, a corresponding NodeId is required for each AggregateFunction.

Bad_AggregateNotSupported

The requested AggregateFunction is not supported by the Server for the specified Node.

Bad_AggregateInvalidInputs

The Aggregate value could not be derived due to invalid data inputs, errors attempting to perform data conversions or similar situations.

Table 9 – Uncertain operation level result codes

Symbolic Id

Description

Uncertain_DataSubNormal

The value is derived from raw values and has less than the required number of Good values.

These bits are set only when obtaining Aggregate data. They indicate where the data value came from and provide information that affects how the client uses the data value. Table 10 lists the bit settings which indicate the data location (i.e. is the value stored in the underlying data repository, or is the value the result of data aggregation). These bits are mutually exclusive.

Table 10 – Data location

StatusCode

Description

Raw

A Raw data value.

Calculated

A data value which was calculated.

Interpolated

A data value which was interpolated.

In the case where Interpolated data is requested, and there is an actual raw value for that timestamp, the Server should set the ‘Raw’ bit in the StatusCode of that value.

Table 11 lists the bit settings which indicate additional important information about the data values returned.

Table 11 – Additional information

StatusCode

Description

Partial

A calculated value that is not based on a complete interval. See 5.3.3.2.

Extra Data

If a Server chooses to set this bit, it indicates that a Raw data value supersedes other data at the same timestamp.

Multiple Values

Multiple values match the Aggregate criteria (i.e. multiple minimum values or multiple worst quality at different timestamps within the same ProcessingInterval).

The conditions under which these information bits are set depend on how the data has been requested and state of the underlying data repository.

Partial bit is used to indicate that the interval is not a complete interval and that a client may receive a different value for the Aggregate if it re-fetches the interval with the same parameters.

The Partial bit will be set in the following examples:

Assume for these examples the first stored point in the collection is 1:01:10 and the last stored point in the collection is 1:31:20. Older data may exist but is unavailable or offline at the time of the query. Newer data may be available but has not yet been stored in the history collection.

  • The interval that overlaps the beginning of the history collection. If the start time is 1:00:00 and end time is 1:10:00 and the interval is 2 minutes then the first interval would have a Partial bit set since it has no data for the first 70 seconds. The Partial bit will always be set for the first interval with data if the start time of the interval is before the first data value of the data collection. For intervals prior to the interval with a Partial bit, these intervals will be flagged Bad_NoData.
  • The interval that overlaps the latest point stored in the history collection. The last point in the collection is 1:31:20 and the historian was not shut down and is still running. A 6-minute interval that started at 1:30:00 would have the Partial bit set because the historian is expecting data, but just has not yet received anything. The Partial bit will always be set for the last interval with data if the end time of the interval is after the last data value stored in the data collection. Intervals entirely after the interval with a Partial bit will be flagged Bad_NoData. For those Aggregates with extrapolation, the Partial bit may be set. See the Aggregate specific characteristics for more details.
  • If the start/end time does not result in an even interval and there is additional data beyond the end time then the last interval will have a Partial bit. If the start time is 1:00:00 and end time is 1:20:00 and the interval is 6 minutes then the last interval is just 2 minutes long and will have the Partial bit set. Extrapolation does not apply in this case.

The Partial bit may be set with the Calculated bit when the Calculated bit is always set for the specific Aggregate.

The purpose of subclause 5.4 is to detail the requirements and behaviour for OPC UA Servers supporting Aggregates. The intent is to standardize the Aggregates so users can reliably predict the results of an Aggregate computation and understand its meaning. If users require custom functionality in the Aggregates, those Aggregates should be written as custom vendor defined Aggregates.

The standard Aggregates shall be as consistent as possible, meaning that each Aggregate’s behaviour shall be similar to every other Aggregate’s behaviour where input parameters, Raw data, and boundary conditions are similar. Where possible, the Aggregates should deal with input and preconditions in a similar manner.

Subclause 5.4 is divided up into two parts. Subclause 5.4.2 deals with Aggregate characteristics and behaviour that are common to all Aggregates. Subclause 5.4.3 deals with the characteristics and behaviour of Aggregates that are aggregate-specific.

Subclause 5.4.2 deals with Aggregate characteristics and behaviour that are common to all Aggregates.

To read Historical Aggregates, OPC clients shall specify three time parameters:

The OPC Server shall use these three parameters to generate a sequence of time intervals and then calculate an Aggregate for each interval. Subclause 5.4.2.2 specifies, given the three parameters, which time intervals are generated. Table 12 provides information on the intervals for each Start and End time combination. The range is defined to be |End - Start|.

All Aggregates return a timestamp of the start of the interval unless otherwise noted for the particular Aggregate.

Table 12 – History Aggregate interval information

Start/End Time

Interval

Resulting intervals

Start = End

Int = Anything

No intervals. Returns a Bad_InvalidArgument StatusCode, regardless of whether there is data at the specified time or not.

Start < End

Int = 0 or IntRange

One interval, starting at Start and ending at End. Includes Start, excludes End, i.e., [Start, End).

Start < End

Int ≠ 0, Int < Range, Int divides Range evenly.

Range/Int intervals. Intervals are [Start, Start + Int), [Start + Int, Start + 2 x Int),..., [End - Int, End).

Start < End

Int ≠ 0, Int < Range, Int does not divide Range evenly.

Range/Int intervals. Intervals are [Start, Start + Int), [Start + Int, Start + 2 x Int),..., [Start + ( Range/Int - 1) x Int, Start + Range/Int x Int), [Start + Range/Int x Int, End).

In other words, the last interval contains the “rest” that remains in the range after taking away Range/Int intervals of size Int.

Start > End

Int = 0 or IntRange

One interval, starting at Start and ending at End. Includes Start, excludes End, i.e.,[Start, End). a

Start > End

Int ≠ 0, Int < Range, Int divides Range evenly.

Range/Int intervals. Intervals are [Start, Start- Int), [Start– Int, Start – 2 x Int),..., [End + Int, End). a

Start > End

Int ≠ 0, Int < Range, Int does not divide Range evenly.

Range/Int intervals. Intervals are [Start, Start - Int), [Start –Int,Start - 2 x Int),..., [Start – ( Range/Int - 1) x Int , Start - Range/Int x Int), [Start - Range/Int x Int , End).

In other words, the last interval contains the “rest” that remains in the range after taking away Range/Int intervals of size Int starting at Start. a

a In this case time is running backwards on the intervals.

The calculation of all Aggregates when time flows backwards is the same as when time flows forwards with the exception that the ‘early time’ is excluded from the interval and the ‘late time’ is included. In most cases this means the value will be the same except the timestamps are shifted by one ProcessingInterval. E.g. when time flows forward the value at T = n is the same as the value at T = n + 1 when time flows backward.

Note that when determining Aggregates with MonitoredItem, the interval is simply the ProcessingInterval parameter as defined in the AggregateFilter structure. See OPC 10000-4 for more details.

Table 13 outlines the valid DataType for each Aggregate. Some Aggregates are intended for numeric data types – i.e. integers or real/floating point numbers. Dates, strings, arrays, etc. are not supported. Other Aggregates are intended for digital data types – i.e. Boolean or enumerations. In addition some Aggregates may return results with a different DataType than those used to calculate the Aggregate. Table 13 also outlines the data type returned for each Aggregate.

Table 13 – Standard History Aggregate Data Type information

BrowseName

Valid Data Type

Result Data Type

Interpolation Aggregate

Interpolative

Numeric

Raw Data Type

Data Averaging Aggregates

Average

Numeric

Double

TimeAverage

Numeric

Double

TimeAverage2

Numeric

Double

Total

Numeric

Double

Total2

Numeric

Double

Data Variation Aggregates

Minimum

Numeric

Raw data type

Maximum

Numeric

Raw data type

MinimumActualTime

Numeric

Raw data type

MaximumActualTime

Numeric

Raw data type

Range

Numeric

Raw data type

Minimum2

Numeric

Raw data type

Maximum2

Numeric

Raw data type

MinimumActualTime2

Numeric

Raw data type

MaximumActualTime2

Numeric

Raw data type

Range2

Numeric

Raw data type

Counting Aggregates

AnnotationCount

All

Integer

Count

All

Integer

DurationInStateZero

Numeric or Boolean

Duration

DurationInStateNonZero

Numeric or Boolean

Duration

NumberOfTransitions

Numeric or Boolean

Integer

Time Aggregates

Start

All

Raw data type

End

All

Raw data type

Delta

Numeric

Raw data type

StartBound

All

Raw data type

EndBound

All

Raw data type

DeltaBounds

Numeric

Raw data type

Data Quality Aggregates

DurationGood

All

Duration

DurationBad

All

Duration

PercentGood

All

Double

PercentBad

All

Double

WorstQuality

All

StatusCode

WorstQuality2

All

StatusCode

Statistical Aggregates

StandardDeviationSample

Numeric

Double

VarianceSample

Numeric

Double

StandardDeviationPopulation

Numeric

Double

VariancePopulation

Numeric

Double

The following issues may come up when calculating Aggregates that include time as part of the calculation.

  • All Aggregate calculations include the startTime but exclude the endTime. However, it is sometimes necessary to return an Interpolated End Bound as the value for an Interval with a timestamp that is in the Interval. Servers are expected to use the time immediately before endTime where the time resolution of the Server determines the exact value (do not confuse this with hardware or operating system time resolution). For example, if the endTime is 12:01:00, the time resolution is 1 second, then the EffectiveEndTime is 12:00:59. If the Server time resolution is 1 millisecond the EffectiveEndTime is 12:00:59.999.

If time is flowing backwards, Servers are expected to use the time immediately after endTime where the time resolution of the Server determines the exact value.

  • If there is one data point in the Interval and it falls on the StartTime the time duration used in calculations is one unit of the time resolution of the Server.

When accessing aggregated data using the HistoryRead or the CreateMonitoredItems Service, the following rules are used to handle specific Aggregate use cases.

If ProcessingInterva l is 0, the Server shall create one Aggregate value for the entire time range. This allows Aggregates over large periods of time. A value with a timestamp equal to endTime will be excluded from that Aggregate, just as it would be excluded from an interval with that ending time. If the ProcessingInterval of 0 is passed in the MonitoredItemFilter it shall be revised to a suitable non-zero value.

The timestamp returned with the Aggregate shall be the time at the beginning of the interval, except where the Aggregate specifies a different timestamp.

If a requested timestamp is set to anything but the source timestamp the operation shall return the Bad_TimestampToReturnInvalid StatusCode. If a requested timestamp is not supported in any other way for a HistoricalDataNode, the operation shall return the Bad_TimestampNotSupported StatusCode. For MonitoredItem the Server shall not return past data if a requested timestamp is not supported by the history collection.

StatusCodes for an Aggregate value shall take into account the values used to calculate them. In addition, the configuration parameters PercentDataGood and PercentDataBad allow the client to control how this calculation is done if supported by the Server.

If an Aggregate operates on raw values (e.g. Average) the calculation is done by counting values. If an Aggregate operates on raw values but can also return a Bounding Value then the Bounding Values are included in the count when computing the StatusCode. If an Aggregate does any sort of a time weighted calculation (e.g. TimeAverage or TimeAverage2) then the StatusCode calculation shall also be time weighted.

For purposes of calculating time weighted StatusCodes each interval shall be divided into regions of Good or Bad data. Creating these regions requires that the bounding values be calculated for each interval and the type of bounding value depends on the Aggregate.

Use the following to determine the StatusCode of a given aggregate. If TreatUncertainAsBad = False then Uncertain regions are included with the Good regions when calculating the above ratios, if the TreatUncertainAsBad = True then the Uncertain regions are included as Bad regions. If no Bad regions are in the interval then the StatusCode for the interval is Good. For any intervals containing regions where the StatusCodes are Bad, the total duration of all Bad regions is calculated and divided by the width of the interval. The resulting ratio is multiplied by 100 and compared to the PercentDataBad parameter. The StatusCode for the interval is Bad if the ratio is greater than or equal to the PercentDataBad parameter. For any interval which is not Bad, the total duration of all Good regions is then calculated and divided by the width of the interval. The resulting ratio is multiplied by 100 and compared to the PercentDataGood parameter. The StatusCode for the interval is Good if the ratio is greater than or equal to the PercentDataGood parameter. If for an interval neither ratio applies then that interval is Uncertain_DataSubNormal.

If there is no data in the interval and the interval is inside the range [start of data, end of data] and the Aggregate return data type is raw data type then the StatusCodes for the interval will be Bad_NoData unless an alternate status code is defined for a specific Aggregate.

The width of an interval is the ProcessingInterval unless it is a partial interval (i.e. has the Partial bit set). In these cases, the width is the time used when calculating the partial interval.

Subclauses 5.4.3.2.2 and 5.4.3.2.3 include diagrams that illustrate a request and data series. The colour of the time axis indicates the status for different regions. Red indicates Bad, green indicates Good and orange indicates Uncertain. These examples assume TreatUncertainAsBad = False.

Figure 2 illustrates a data series for Variable with Stepped = False and an Aggregate that uses Simple Bounding Values. The request being processed has a Start Time that falls before the first point in the series and an End Time that does not fall on an integer multiple of the ProcessingInterval.

image005.png

Figure 2 – Variable with Stepped = False and Simple Bounding Values

The first interval has four regions:

A region is Uncertain if a region ends in a Bad or Uncertain value and SlopedInterpolation is used. The end point has no effect on the region if SteppedInterpolation is used.

The second interval has three regions:

  • the period before the first Good data point where no data exists;
  • the period between the first and second where SlopedInterpolation can be used;
  • the period between the second point and the bound calculated with SlopedInterpolation.

The third interval has three regions:

  • the period between the simple bound and the first data point;
  • the period between the first point and an interpolated point that falls on the end time;
  • the period after the end time which is ignored.

This is a partial region and the data after the end time is not used, however, if sloped interpolation is used and the point after the endpoint is Uncertain then the region between the last point and the end time will be Uncertain.

Figure 3 illustrates a data series for Variable with Stepped = True and an Aggregate that uses Interpolated Bounding Values. The request being processed has a Start Time that falls before the first point in the series and an End Time that does not fall on an integer multiple of the ProcessingInterval.

image006.png

Figure 3 – Variable with Stepped = True and Interpolated Bounding Values

The first interval has three regions:

The Bad point is ignored because of the interpolated end bound but this does create Uncertain regions. If SlopedInterpolation was used the Uncertain region would start at the second point. In this case, it only starts when the first Bad value is ignored.

The second interval has three regions:

  • the period between the start bound and the first data point;
  • the period between the first and second where SteppedInterpolation is used;
  • the period between the second and the interpolated end bound.

The third interval has three regions:

  • the period between the interpolated bound and the first data point;
  • the period between the first point and an interpolated point that falls on the end time;
  • the period after the end time which is ignored.

This is a partial region and the data after the end time is not used.

Subclause 5.4.3.3 deals with Aggregate specific characteristics and behaviour that is specific to a particular Aggregate.

Each subclause has a table which formally expresses the Aggregate behaviour (including any exceptions). The meaning of each of the fields in the table is described in Table 14.

Description of Table 14:

  • The first column is the common name for the item.
  • The second column includes a description of the item and a list of the valid selections with for the item including a description of each selection.
  • The second part of the table describes how the status associated with the Aggregate calculation is computed.
  • The last part of the table lists what behaviour is expected from the Aggregate for some common special cases. These behaviours require text descriptions so there is no list of valid selections.

Table 14 – Aggregate table description

Aggregate Characteristics

Type

The type of Aggregate.

<Interpolated | Calculated | Raw>

Interpolated: See definition for Interpolated.

Calculated: Computed from defined calculation.

Raw: Selects a raw value from within an interval.

Data Type

The data type of the result.

<Double | Int32 | Same as Source>

Use Bounds

How the Aggregate deals with bounds.

<None | Interpolated | Simple>

None: Bounds do not apply to the Aggregate.

Interpolated: Uses Interpolated Bounds.

Simple: Uses Simple Bounds.

Timestamp

What is the time stamp of the resulting Aggregate value:

<startTime | endTime | Raw>

startTime: The time at the start of the interval.

endTime: The time at the end of the interval.

Raw: The time associated with a value in the interval.

StatusCode Calculations

Calculation Method

How the status code is calculated:

<PercentValues | PercentTime | Custom>

PercentValues: Based on percentage of value counts.

PercentTime: Based on percentage of time interval.

Custom: Specific to the Aggregate (description included).

Partial

For partial intervals does the Aggregate set this bit

<Set Sometimes | Not Set>

It may also describe any special cases for setting this bit

Calculated

Describes the usage of the calculated bit.

<Set Always | Set Sometimes | Not Set>

Set Always: The bit is always set.

Set Sometimes: The bit is sometimes set (describes when).

Not Set: The bit is never set.

Interpolated

Describes the usage of the interpolated bit.

<Set Always | Set Sometimes | Not Set>

Set Always: The bit is always set.

Set Sometimes: The bit is sometimes set (describes when).

Not Set: The bit is never set.

Raw

Describes the usage of the Raw bit.

<Set Always | Set Sometimes | Not Set>

Set Always: The bit is always set.

Set Sometimes: The bit is sometimes set (describes when).

Not Set: The bit is never set.

Multi Value

Describes the usage of the multi value bit.

<Set Sometimes | Not Set>

Set Sometimes: The bit is used (see OPC 10000-11).

Not Set: The bit is never set.

StatusCode Common Special Cases

Before Start of Data

If the entire interval is before the start of data.

After End of Data

If the entire interval is after the end of data (as determined by the Historian).

Start Bound Not Found

If the starting bound is not found for the earliest interval and it is not partial, then what, if any, special processing should be done.

End Bound Not Found

If the ending bound is not found for the latest interval and it is not partial, then what, if any, special processing should be done.

Bound Bad

If the Bounding value is Bad, then what, if any, special processing should be done.

Bound Uncertain

If the Bounding value is uncertain, then what, if any, special processing should be done.

The Interpolative Aggregate defined in Table 15 returns the Interpolated Bounding Value (see 3.1.8) for the startTime of each interval.

When searching for Good values before or after the bounding value, the time period searched is Server specific, but the Server should search a time range which is at least the size of the ProcessingInterval.

Table 15 – Interpolative Aggregate summary

Interpolated Aggregate Characteristics

Type

Interpolated

Data Type

Same as Source

Use Bounds

Interpolated

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Good if no Bad values skipped and Good values are used, Uncertain if Bad values skipped or if Uncertain values are used. If no starting value then Bad_NoData. See description of Interpolated Bounds (see 3.1.8) for more details

Partialbit

Not Set

Calculated bit

Not Set

Interpolated bit

Set Sometimes

Always set except for when the Raw bit is set

Raw bit

Set Sometimes

If a value exists with the exact time of interval Start

Multi Value bit

Not Set

StatusCode Common Special Cases

Before Start of Data

Return Bad_NoData

After End of Data

Return extrapolated value (see 3.1.8) (sloped or stepped according to settings)

Status code is Uncertain_DataSubNormal.

Start Bound Not Found

Bad_NoData.

End Bound Not Found

See “After End of Data”

Bound Bad

Does not return a Bad bound except as noted above

Bound Uncertain

Returned Uncertain_DataSubNormal if any Bad value(s) was/were skipped to calculate the bounding value.

The Average Aggregate defined in Table 16 adds up the values of all Good Raw data for each interval, and divides the sum by the number of Good values. If any non-Good values are ignored in the computation, the Aggregate StatusCode will be determined using the StatusCode Calculation (see 5.3). This Aggregate is not time based so the PercentGood/PercentBad applies to the number of values in the interval.

Table 16 – Average Aggregate summary

Average Aggregate Characteristics

Type

Calculated

Data Type

Double

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

PercentValues

Partial

Not Set

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Bounds not used

No End Bound

Bounds not used

Bound Bad

Bounds not used

Bound Uncertain

Bounds not used

The TimeAverage Aggregate defined in Table 17 uses Interpolated Bounding Values (see 3.1.8) to find the value of a point at the beginning and end of an interval. Starting at the starting bounding value a straight line is drawn between each value in the interval ending at the ending bounding value (see examples for illustrations). The area under the lines is divided by the length of the ProcessingInterval to yield the average. Note that this calculation always uses a sloped line between points; TimeAverage2 uses a stepped or sloped line depending on the value of the Stepped Property for the Variable.

If one or more Bad Values exist in the interval then they are omitted from the calculation and the StatusCode is set to Uncertain_DataSubNormal. Sloped lines are drawn between the Good values when calculating the area.

The time resolution used in this calculation is Server specific.

Table 17 – TimeAverage Aggregate summary

TimeAverage Aggregate Characteristics

Type

Calculated

Data Type

Double

Use Bounds

Interpolated

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Good if no Bad values skipped and Good values are used, Uncertain if Bad values are skipped or if Uncertain values are used

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Value extrapolated, Uncertain status

No Start Bound

Calculate Partial Interval

No End Bound

Extrapolate data, Uncertain status

Bound Bad

NA

Bound Uncertain

NA

The TimeAverage2 Aggregate defined in Table 18 uses Simple Bounding Values (see 3.1.9) to find the value of a point at the beginning and end of an interval. Starting at the starting bounding value a straight line is drawn between each value in the interval ending at the ending bounding value (see examples for illustrations). The area under the lines is divided by the length of the ProcessingInterval to yield the average. Note that this calculation uses a stepped or sloped line depending on what the value of the Stepped Property for the Variable; TimeAverage always uses a sloped line between points.

The time resolution used in this calculation is Server specific.

If any non-Good data exists in the interval, this data is omitted from the calculation and the time interval is reduced by the duration of the non-Good data; i.e. if a value was Bad for 1 minute in a 5-minute interval then the TimeAverage2 would be the area under the 4-minute period of Good values divided by 4 minutes. If a sub-interval ends at a Bad value then only the Good starting value is used to calculate the area of sub-interval preceding the Bad value.

The Aggregate StatusCode will be determined using the StatusCode Calculation (see 5.3).

Table 18 – TimeAverage2 Aggregate summary

TimeAverage2 Aggregate Characteristics

Type

Calculated

Data Type

Double

Use Bounds

Simple

Timestamp

StartTime

StatusCode Calculations

Calculation Method

PercentTime

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Bound is Bad_NoData and treated as any other Bad value in the interval

No End Bound

Bound is Bad_NoData and treated as any other Bad value in the interval

Bound Bad

Treated as any other Bad value in the interval

Bound Uncertain

Treated as any other Uncertain value in the interval

The Total Aggregate defined in Table 19 performs the following calculation for each interval:

Total = TimeAverage x ProcessingInterval (seconds)

where: TimeAverage is the result from the TimeAverage Aggregate, using the ProcessingInterval supplied to the Total call.

The resulting units would be normalized to seconds, i.e. [TimeAverage Units] x seconds.

The Aggregate StatusCode will be determined using the StatusCode Calculation (see 5.3).

Note that this calculation always uses a SlopedInterpolation between points; Total2 uses a Stepped Attribute or SlopedInterpolation depending on the value of the Stepped Attribute for the Variable.

Table 19 – Total Aggregate summary

Total Aggregate Characteristics

Type

Calculated

Data Type

Double

Use Bounds

Interpolated

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Good if no Bad values are skipped and Good values are used, Uncertain if Bad values are skipped or if Uncertain values are used

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Value extrapolated, Uncertain status

No Start Bound

Calculate Partial Interval

No End Bound

Extrapolate data, Uncertain status

Bound Bad

NA

Bound Uncertain

NA

The Total2 Aggregate defined in Table 20 performs the following calculation for each interval:

Total2 = TimeAverage2 x ProcessingInterval of Good data (seconds)

where TimeAverage2 is the result from the TimeAverage2 Aggregate, using the ProcessingInterval supplied to the Total2 call.

The interval of Good data is the sum of all sub-intervals where non-Bad data exists; i.e. if a value was Bad for 1 minute in a 5-minute interval then the interval of Good data would be the 4-minute period.

The resulting units would be normalized to seconds, i.e. [TimeAverage2 Units] x seconds.

The Aggregate StatusCode will be determined using the StatusCode Calculation (see 5.3).

Table 20 – Total2 Aggregate summary

Total2 Aggregate Characteristics

Type

Calculated

Data Type

Double

Use Bounds

Simple

Timestamp

StartTime

StatusCode Calculations

Calculation Method

PercentTime

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Value for Bound is Bad_NoData and is treated like any other Bad quality value in the calculation (ignored)

No End Bound

Value for Bound is Bad_NoData and is treated like any other Bad quality value in the calculation (ignored)

Bound Bad

Value is treated like any other Bad quality value in the calculation (ignored)

Bound Uncertain

Value is treated like any other non-Good quality value in the calculation (ignored)

The Minimum Aggregate defined in Table 21 retrieves the minimum Good raw value within the interval, and returns that value with the timestamp at the start of the interval. Note that if the same minimum exists at more than one timestamp the MultipleValues bit is set.

Unless otherwise indicated, StatusCodes are Good, Calculated. If the minimum value is on the start time the status code will be Good, Raw. If only Bad quality values are available then the status is returned as Bad_NoData.

The timestamp of the Aggregate will always be the start of the interval for every ProcessingInterval.

Table 21 – Minimum Aggregate summary

Minimum Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

If no Bad values then the Status is Good. If Bad values exist then the Status is Uncertain_SubNormal. If an Uncertain value is less than the minimum Good value the Status is Uncertain_SubNormal.

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Sometimes

If the Minimum value is not on the StartTime of the interval or if the Status was set to Uncertain_SubNormal because of non-Good values in the interval

Interpolated

Not Set

Raw

Set Sometimes

If Minimum value is on the StartTime of the interval

Multi Value

Set Sometimes

If multiple Good values exist with the Minimum value

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Not Applicable

No End Bound

Not Applicable

Bound Bad

Not Applicable

Bound Uncertain

Not Applicable

The Maximum Aggregate defined in Table 22 retrieves the maximum Good raw value within the interval, and returns that value with the timestamp at the start of the interval. Note that if the same maximum exists at more than one timestamp the MultipleValues bit is set.

Unless otherwise indicated, StatusCodes are Good, Calculated. If the maximum value is on the interval start time the status code will be Good, Raw. If only Bad quality values are available then the status is returned as Bad_NoData.

The timestamp of the Aggregate will always be the start of the interval for every ProcessingInterval.

Table 22 – Maximum Aggregate summary

Maximum Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

If no Bad values then the Status is Good. If Bad values exist then the Status is Uncertain_SubNormal. If an Uncertain value is greater than the maximum Good value the Status is Uncertain_SubNormal

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Sometimes

If the Maximum value is not on the startTime of the interval or if the Status was set to Uncertain_SubNormal because of non-Good values in the interval

Interpolated

Not Set

Raw

Set Sometimes

If Maximum value is on the startTime of the interval

Multi Value

Set Sometimes

If multiple Good values exist with the Maximum value

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Not Applicable

No End Bound

Not Applicable

Bound Bad

Not Applicable

Bound Uncertain

Not Applicable

The MinimumActualTime Aggregate defined in Table 23 retrieves the minimum Good raw value within the interval, and returns that value with the timestamp at which that value occurs. Note that if the same minimum exists at more than one timestamp, the oldest one is retrieved and the Aggregate Bits are set to MultipleValues.

Table 23 – MinimumActualTime Aggregate summary

MinimumActualTime Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

None

Timestamp

Time of Minimum

StatusCode Calculations

Calculation Method

Custom

If no Bad values then the Status is Good. If Bad values exist then the Status is Uncertain_SubNormal. If an Uncertain value is less than the minimum Good value the Status is Uncertain_SubNormal

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Sometimes

If the Status was set to Uncertain_SubNormal because of non-Good values in the interval

Interpolated

Not Set

Raw

Set Sometimes

If a Good minimum value is returned

Multi Value

Set Sometimes

If multiple Good values exist with the Minimum value

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Not Applicable

No End Bound

Not Applicable

Bound Bad

Not Applicable

Bound Uncertain

Not Applicable

The MaximumActualTime Aggregate defined in Table 24 is the same as the MinimumActualTime Aggregate, except that the value is the maximum raw value within the interval. Note that if the same maximum exists at more than one timestamp, the oldest one is retrieved and the Aggregate Bits are set to MultipleValues.

Table 24 – MaximumActualTime Aggregate summary

MaximumActualTime Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

None

Timestamp

Time of Maximum

StatusCode Calculations

Calculation Method

Custom

If no Bad values then the Status is Good. If Bad values exist then the Status is Uncertain_SubNormal. If an Uncertain value is greater than the maximum Good value the Status is Uncertain_SubNormal

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Sometimes

If the Status was set to Uncertain_SubNormal because of non-Good values in the interval

Interpolated

Not Set

Raw

Set Sometimes

If a Good maximum value is returned

Multi Value

Set Sometimes

If multiple Good values exist with the maximum value

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Not Applicable

No End Bound

Not Applicable

Bound Bad

Not Applicable

Bound Uncertain

Not Applicable

The Range Aggregate defined in Table 25 finds the difference between the maximum and minimum Good raw values in the interval. If only one Good value exists in the interval, the range is zero. Note that the range is always zero or positive. If non-Good values are ignored when finding the minimum or maximum values or if Bad values exist then the status is Uncertain_DataSubNormal.

Table 25 – Range Aggregate summary

Range Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

If no Bad values then the Status is Good. If Bad values exist then the Status is Uncertain_SubNormal. If an Uncertain value is greater than the maximum or less than the minimum Good value the Status is Uncertain_SubNormal

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Not Applicable

No End Bound

Not Applicable

Bound Bad

Not Applicable

Bound Uncertain

Not Applicable

The Minimum2 Aggregate defined in Table 26 retrieves the minimum Good value for each interval as defined for Minimum except that Simple Bounding Values are included. The Simple Bounding Values for the interval are found according to the definition of Simple Bounding Values (see 3.1.9). Any Bad values are ignored in the computation. The Aggregate StatusCode will be determined using the StatusCode Calculation (see 5.3) for time based Aggregates. If a bounding value is returned then the status will indicate, Raw, Calculated or Interpolated.

If TreatUncertainAsBad is false and an Uncertain raw value is the minimum then that Uncertain value is used. Uncertain values are ignored otherwise.

If sloped interpolation is used and the End bound is the minimum value then End bound is used as the Minimum with the timestamp set to the startTime of the interval. The End bound is ignored in all other cases.

Table 26 – Minimum2 Aggregate summary

Minimum2 Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

Simple

Timestamp

StartTime

StatusCode Calculations

Calculation Method

PercentTime

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set SometimesSet unless the StartBound is the Minimum

Interpolated

Set Sometimes

If an Interpolated bound is the Minimum

Raw

Set Sometimes

If a raw value is the Minimum.

Multi Value

Set Sometimes

If more than one Good values exist with the same

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Treat the beginning value as Bad_NoData and compute the Aggregate

No End Bound

Treat the ending value as Bad_NoData and compute the Aggregate

Bound Bad

Use as value and compute the Aggregate as defined

Bound Uncertain

Use as value and compute the Aggregate as defined

The Maximum2 Aggregate defined in Table 27 retrieves the maximum Good value for each interval as defined for Maximum except that Simple Bounding Values are included. The Simple Bounding Values for the interval are found according to the definition of Simple Bounding Values (see 3.1.9). Any Bad values are ignored in the computation. The Aggregate StatusCode will be determined using the StatusCode Calculation (see 5.3) for time based Aggregates. If a bounding value is returned then the status will indicate, Raw, Calculated or Interpolated.

If TreatUncertainAsBad is false and an Uncertain raw value is the maximum then that Uncertain value is used. Uncertain values are ignored otherwise.

If sloped interpolation is used and the End bound is the maximum value then End bound is used as the maximum with the timestamp set to the startTime of the interval. The End bound is ignored in all other cases.

Table 27 – Maximum2 Aggregate summary

Maximum2 Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

Simple

Timestamp

StartTime

StatusCode Calculations

Calculation Method

PercentTime

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Sometimes

Set unless the StartBound is the Maximum

Interpolated

Set Sometimes

If an Interpolated bound is the Maximum

Raw

Set Sometimes

If a raw value is the Maximum.

Multi Value

Set Sometimes

If more than one Good values exist with the same

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Treat the beginning value as Bad_NoData and compute the Aggregate

No End Bound

Treat the ending value as Bad_NoData and compute the Aggregate

Bound Bad

Use as value and compute the Aggregate as defined

Bound Uncertain

Use as value and compute the Aggregate as defined

The MinimumActualTime2 Aggregate defined in Table 28 retrieves the minimum Good value for each interval as defined for MinimumActualTime except that Simple Bounding Values are included. The Simple Bounding Values for the interval are found according to the definition of Simple Bounding Values (see 3.1.9). Any Bad values are ignored in the computation. The Aggregate StatusCode will be determined using the StatusCode Calculation (see 5.3) for time based Aggregates. If a bounding value is returned then the status will indicate, Raw, Calculated or Interpolated.

If TreatUncertainAsBad is false and an Uncertain raw value is the minimum then that Uncertain value is used. Uncertain values are ignored otherwise.

If sloped interpolation is used and the End bound is the minimum value then End bound is used as the minimum with the timestamp set to the EffectiveEndTime of the interval. The End bound is ignored in all other cases.

Table 28 – MinimumActualTime2 Aggregate summary

MinumumActualTime2 Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

Simple

Timestamp

Time of minimum

StatusCode Calculations

Calculation Method

PercentTime

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Not Set

Interpolated

Set Sometimes

If an Interpolated bound is the Minimum

Raw

Set Sometimes

If a raw value is the Minimum

Multi Value

Set Sometimes

If more than one Good values exist with the same value

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Treat the beginning value as Bad_NoData and compute the Aggregate

No End Bound

Treat the ending value as Bad_NoData and compute the Aggregate

Bound Bad

Use as value and compute the Aggregate as defined

Bound Uncertain

Use as value and compute the Aggregate as defined

The MaximumActualTime2 Aggregate defined in Table 29 retrieves the maximum Good value for each interval as defined for MaximumActualTime except that Simple Bounding Values are included. The Simple Bounding Values for the interval are found according to the definition of Simple Bounding Values (see 3.1.9). Any Bad values are ignored in the computation. The Aggregate StatusCode will be determined using the StatusCode Calculation (see 5.3) for time based Aggregates. If a bounding value is returned then the status will indicate, Raw, Calculated or Interpolated.

If TreatUncertainAsBad is false and an Uncertain raw value is the maximum then that Uncertain value is used. Uncertain values are ignored otherwise.

If sloped interpolation is used and the End bound is the maximum value then End bound is used as the maximum with the timestamp set to the EffectiveEndTime of the interval. The End bound is ignored in all other cases.

Table 29 – MaximumActualTime2 Aggregate summary

MaximumActualTime2 Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

Simple

Timestamp

Time of maximum

StatusCode Calculations

Calculation Method

PercentTime

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Not Set

Interpolated

Set Sometimes

If an Interpolated bound is the Maximum

Raw

Set Sometimes

If a raw value is the Maximum

Multi Value

Set Sometimes

If more than one value is equal to the Maximum

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Treat the beginning value as Bad_NoData and compute the Aggregate

No End Bound

Treat the ending value as Bad_NoData and compute the Aggregate

Bound Bad

Use as value and compute the Aggregate as defined

Bound Uncertain

Use as value and compute the Aggregate as defined

The Range2 Aggregate defined in Table 30 finds the difference between the maximum and minimum values in the interval as returned by the Minimum2 and Maximum2 Aggregates. Note that the range is always zero or positive.

Table 30 – Range2 Aggregate summary

Range2 Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

Simple (used in Minimum2 and Maximum2 calculations)

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

If Minimum2 or Maximum2 are Bad then the status is Bad_NoData. If Minimum2 or Maximum2 are Uncertain then the status is Uncertain_DataSubNormal. Good otherwise

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Handled by Minimum2 and Maximum2

No End Bound

Handled by Minimum2 and Maximum2

Bound Bad

Handled by Minimum2 and Maximum2

Bound Uncertain

Handled by Minimum2 and Maximum2

The AnnotationCount Aggregate defined in Table 31 returns a count of all Annotations in the interval.

The StatusCodes are Good, Calculated.

Table 31 – AnnotationCount Aggregate summary

AnnotationCount Aggregate Characteristics

Type

Calculated

Data Type

Int32 (negative values are not allowed)

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Good unless the interval is before the start of data or after the end of data

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Does not apply

No End Bound

Does not apply

Bound Bad

Does not apply

Bound Uncertain

Does not apply

The Count Aggregate defined in Table 32 retrieves a count of all the raw values within an interval. If one or more raw values are non-Good, they are not included in the count, and the Aggregate StatusCode is determined using the StatusCode Calculation (see 5.4.3) for non-time based Aggregates. If no Good data exists for an interval, the count is zero.

Unless otherwise indicated, StatusCodes are Good, Calculated.

Table 32 – Count Aggregate summary

Count Aggregate Characteristics

Type

Calculated

Data Type

Int32 (negative values are not allowed)

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

PercentValues

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Does not apply

No End Bound

Does not apply

Bound Bad

Does not apply

Bound Uncertain

Does not apply

The DurationInStateZero Aggregate defined in Table 33 returns the time Duration during the interval that the Variable was in the zero state. The Simple Bounding Values for the interval are used to determine initial value (start time < end time) or ending value (if start time > end time). If one or more raw values are non-Good, they are not included in the Duration, and the Aggregate StatusCode is determined using the StatusCode Calculation (see 5.3) for time based Aggregates. Duration is in milliseconds. Unless otherwise indicated, StatusCodes are Good, Calculated.

Table 33 – DurationInStateZero Aggregate summary

DurationInStateZero Aggregate Characteristics

Type

Calculated

Data Type

Duration

Use Bounds

Simple

Timestamp

StartTime

StatusCode Calculations

Calculation Method

PercentTime

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Treat the beginning value as Bad_NoData and compute the Aggregate

No End Bound

Treat the ending value as Bad_NoData and compute the Aggregate

Bound Bad

Use as value and compute the Aggregate as defined

Bound Uncertain

Use as value and compute the Aggregate as defined

The DurationInStateNonZero Aggregate defined in Table 34 returns the time Duration during the interval that the Variable was in the one state. The Simple Bounding Values for the interval are used to determine initial value (start time < end time) or ending value (if start time > end time). If one or more raw values are non-Good, they are not included in the Duration, and the Aggregate StatusCode is determined using the StatusCode Calculation (see 5.3) for time based Aggregates.

Duration is in milliseconds. Unless otherwise indicated, StatusCodes are Good, Calculated.

Table 34 – DurationInStateNonZero Aggregate summary

DurationInStateNonZero Aggregate Characteristics

Type

Calculated

Data Type

Duration

Use Bounds

Simple

Timestamp

StartTime

StatusCode Calculations

Calculation Method

PercentTime

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Treat the beginning value as Bad_NoData and compute the Aggregate

No End Bound

Treat the ending value as Bad_NoData and compute the Aggregate

Bound Bad

Use as value and compute the Aggregate as defined

Bound Uncertain

Use as value and compute the Aggregate as defined

The NumberOfTransitions Aggregate defined in Table 35 returns a count of the number of transition the Variable had during the interval. If one or more raw values are Bad, they are not included in the count, and the Aggregate StatusCode is determined using the StatusCode Calculation (see 5.3) for non-time based Aggregates.

The earliest transition shall be calculated by comparing the earliest non-Bad value in the interval to the previous non-Bad value. A transition occurred if no previous non-Bad value exists or if the earliest non-Bad value is different. The endTime is not considered part of the interval, so a transition occurring at the endTime is not included.

Unless otherwise indicated, StatusCodes are Good, Calculated.

Table 35 – NumberOfTransitions Aggregate summary

NumberOfTransitions Aggregate Characteristics

Type

Calculated

Data Type

Int32 (negative values are not allowed)

Use Bounds

Custom, a non-Bad value prior to the interval is used

Timestamp

StartTime

StatusCode Calculations

Calculation Method

PercentValues

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Treat the beginning value as Bad_NoData and compute the Aggregate

No End Bound

Treat the ending value as Bad_NoData and compute the Aggregate

Bound Bad

Use as value and compute the Aggregate as defined

Bound Uncertain

Use as value and compute the Aggregate as defined

The Start Aggregate defined in Table 36 retrieves the earliest raw value within the interval, and returns that value and status with the timestamp at which that value occurs. If no values are in the interval then the StatusCode is Bad_NoData.

Table 36 – Start Aggregate summary

Start Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

None

Timestamp

Time of Raw Value

StatusCode Calculations

Calculation Method

Custom

The raw value status is returned

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Not Set

Interpolated

Not Set

Raw

Always

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Does not apply

No End Bound

Does not apply

Bound Bad

Does not apply

Bound Uncertain

Does not apply

The End Aggregate defined in Table 37 retrieves the latest raw value within the interval, and returns that value and status with the timestamp at which that value occurs. If no values are in the interval then the StatusCode is Bad_NoData.

Table 37 – End Aggregate summary

End Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

None

Timestamp

Time of Raw Value

StatusCode Calculations

Calculation Method

Custom

The raw value status is returned

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Not Set

Interpolated

Not Set

Raw

Always

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Does not apply

No End Bound

Does not apply

Bound Bad

Does not apply

Bound Uncertain

Does not apply

The Delta Aggregate defined in Table 38 retrieves the difference between the earliest and latest Good raw values in the interval. The Aggregate is negative if the latest value is less than the earliest value. The status is Uncertain_DataSubNormal if non-Good values are skipped while looking for the first or last values. The status is Good otherwise. The status is Bad_NoData if no Good raw values exist.

Table 38 – Delta Aggregate summary

Delta Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Uncertain_DataSubNormal if non-Good values are skipped while looking for the first or last values

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Does not apply

No End Bound

Does not apply

Bound Bad

Does not apply

Bound Uncertain

Does not apply

The StartBound Aggregate defined in Table 39 returns the value and status at the StartTime for the interval by calculating the Simple Bounding Values for the interval (see 3.1.9).

Table 39 – StartBound Aggregate summary

StartBound Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

Simple

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

The status of the start bound.

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Not Set

Interpolated

Set Sometimes

If the bound is interpolated

Raw

Set Sometimes

If a value exists at the start time

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Bad_NoData

No End Bound

Does not apply

Bound Bad

Same as bound

Bound Uncertain

Same as bound

The EndBound Aggregate defined in Table 40 returns the value and status at the EndTime for the interval by calculating the Simple Bounding Values for the interval (see 3.1.9).

The timestamp returned is always the start of the interval and Calculated bit is set.

Table 40 – EndBound Aggregate summary

EndBound Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

Simple

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

The status of the end bound.

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Does not apply

No End Bound

Bad_NoData

Bound Bad

Same as bound

Bound Uncertain

Same as bound

The DeltaBounds Aggregate defined in Table 41 returns the difference between the StartBound and the EndBound Aggregates with the exception that both the start and end shall be Good. If the end value is less than the start value, the result will be negative. If the end value is the same as the start value the result will be zero. If the end value is greater than the start value, the result will be positive. If one or both values are Bad the return status will be Bad_NoData. If one or both values are Uncertain the status will be Uncertain_DataSubNormal.

Table 41 – DeltaBounds Aggregate summary

DeltaBounds Aggregate Characteristics

Type

Calculated

Data Type

Same as Source

Use Bounds

Simple

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Good if both bounds are Good

Uncertain_DataSubNormal if either bound is uncertain

Bad_NoData if either bound is Bad

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

Bad_NoData

No End Bound

Bad_NoData

Bound Bad

Bad_NoData

Bound Uncertain

Uncertain_DataSubNormal

The DurationGood Aggregate defined in Table 42 divides the interval into regions of Good and non-Good data. Each region starts with a data point in the interval. If that data point is Good the region is Good. The Aggregate is the sum of the duration of all Good regions expressed in milliseconds.

The status of the first region is determined by finding the first data point at or before the start of the interval. If no value exists, the first region is Bad.

Each Aggregate is returned with timestamp of the start of the interval. StatusCodes are Good, Calculated.

Table 42 – DurationGood Aggregate summary

DurationGood Aggregate Characteristics

Type

Calculated

Data Type

Duration

Use Bounds

Uses status of bounding value

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

StatusCode is always Good, Calculated

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

No special handing required

No End Bound

No special handing required

Bound Bad

No special handing required

Bound Uncertain

No special handing required

The DurationBad Aggregate defined in Table 43 divides the interval into regions of Bad and non-Bad data. Each region starts with a data point in the interval. If that data point is Bad the region is Bad. The Aggregate is the sum of the duration of all Bad regions expressed in milliseconds.

The status of the first region is determined by finding the first data point at or before the start of the interval. If no value exists, the first region is Bad.

Each Aggregate is returned with timestamp of the start of the interval. StatusCodes are Good, Calculated.

Table 43 – DurationBad Aggregate summary

DurationBad Aggregate Characteristics

Type

Calculated

Data Type

Duration

Use Bounds

Uses status of bounding value

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

StatusCode is always Good, Calculated

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

No special handing required

No End Bound

No special handing required

Bound Bad

No special handing required

Bound Uncertain

No special handing required

The PercentGood Aggregate defined in Table 44 performs the following calculation:

PercentGood = DurationGood / ProcessingInterval x 100

where:

DurationGood is the result from the DurationGood Aggregate, calculated using the ProcessingInterval supplied to PercentGood call.

ProcessingInterval is the duration of interval.

If the last interval is a partial interval then the duration of the partial interval is used in the calculation. Each Aggregate is returned with timestamp of the start of the interval. StatusCodes are Good, Calculated.

Table 44 – PercentGood Aggregate summary

PercentGood Aggregate Characteristics

Type

Calculated

Data Type

Double (percent)

Use Bounds

Simple (used in DurationGood calculation)

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Always Good

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

No special handing required

No End Bound

No special handing required

Bound Bad

No special handing required

Bound Uncertain

No special handing required

The PercentBad Aggregate defined in Table 45 performs the following calculation:

PercentBad = DurationBad / ProcessingInterval x 100

where:

DurationBad is the result from the DurationBad Aggregate, calculated using the ProcessingInterval supplied to PercentBad call.

ProcessingInterval is the duration of interval.

If the last interval is a partial interval then the duration of the partial interval is used in the calculation. Each Aggregate is returned with timestamp of the start of the interval. StatusCodes are Good, Calculated.

Table 45 – PercentBad Aggregate summary

PercentBad Aggregate Characteristics

Type

Calculated

Data Type

Double (percent)

Use Bounds

Simple (used in DurationBad calculation)

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Always Good.

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

No special handing required

No End Bound

No special handing required

Bound Bad

No special handing required

Bound Uncertain

No special handing required

The WorstQuality Aggregate defined in Table 46 returns the worst status of the raw values in the interval where a Bad status is worse than Uncertain, which is worse than Good. No distinction is made between the specific reasons for the status. The server shall ignore the TreatUncertainAsBad for this aggregate.

If multiple values exist with the worst quality the MultipleValues bit is set. If multiple values exist with the worst quality but different StatusCodes then the StatusCode of the first value is returned.

This Aggregate returns the worst StatusCode as the value of the Aggregate.

The timestamp is always the start of the interval. The StatusCodes are Good, Calculated.

Table 46 – WorstQuality Aggregate summary

WorstQuality Aggregate Characteristics

Type

Calculated

Data Type

StatusCode

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Always Good

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Used

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

No special handing required

No End Bound

No special handing required

Bound Bad

No special handing required

Bound Uncertain

No special handing required

The WorstQuality2 Aggregate defined in Table 47 returns the worst status of the raw values in the interval where a Bad status is worse than Uncertain, which is worse than Good. No distinction is made between the specific reasons for the status. The server shall ignore the TreatUncertainAsBad for this aggregate.

The start bound calculated using Simple Bounding Values (see 3.1.9) is always included when determining the worst quality.

If multiple values exist with the worst quality the MultipleValues bit is set. If multiple values exist with the worst quality but different StatusCodes then the StatusCode of the first value is returned.

This Aggregate returns the worst StatusCode as the value of the Aggregate.

The timestamp is always the start of the interval. The StatusCodes are Good, Calculated.

Table 47 – WorstQuality2 Aggregate summary

WorstQuality2 Aggregate Characteristics

Type

Calculated

Data Type

StatusCode

Use Bounds

Simple

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Always Good

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Used

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

No special handing required

No End Bound

No special handing required

Bound Bad

No special handing required

Bound Uncertain

No special handing required

The StandardDeviationSample Aggregate defined in Table 48 uses the formula:

image007.png

where X is each Good raw value in the interval, Avg(X) is the average of the Good raw values, and n is the number of Good raw values in the interval.

For every interval where n = 1, a value of 0 is returned.

If any non-Good values were ignored, the Aggregate quality is uncertain/subnormal.

All interval Aggregates return timestamp of the start of the interval. Unless otherwise indicated, qualities are Good, Calculated.

This calculation is for a sample population where the calculation is done on a subset of the full set of data. Use StandardDeviationPopulation to calculate the standard deviation of a full set of data (see 5.4.3.39). An example would be when the underlying data is sampled from the data source versus stored on an exception basis.

Table 48 – StandardDeviationSample Aggregate summary

StandardDeviationSample Aggregate Characteristics

Type

Calculated

Data Type

Double

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Always Good

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

No special handing required

No End Bound

No special handing required

Bound Bad

No special handing required

Bound Uncertain

No special handing required

Conformance Units

Aggregates StandardDeviationSample

The VarianceSample Aggregate defined in Table 49 retrieves the square of the standard deviation. Its behaviour is the same as the StandardDeviationSample Aggregate. Unless otherwise indicated, qualities are Good, Calculated.

This calculation is for a sample population where the calculation is done on a subset of the full population. Use VariancePopulation to calculate the variance of a full set of data (5.4.3.40).

Table 49 – VarianceSample Aggregate summary

VarianceSample Aggregate Characteristics

Type

Calculated

Data Type

Double

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Always Good

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

No special handing required

No End Bound

No special handing required

Bound Bad

No special handing required

Bound Uncertain

No special handing required

The StandardDeviationPopulation Aggregate defined in Table 50 uses the formula:

image008.png

where X is each Good raw value in the interval, Avg(X) is the average of the Good raw values, and n is the number of Good raw values in the interval.

For every interval where n = 1, a value of 0 is returned.

If any non-Good values were ignored, the Aggregate quality is uncertain/subnormal.

All interval Aggregates return timestamp of the start of the interval. Unless otherwise indicated, qualities are Good, Calculated.

This calculation is for a full population where the calculation is done on the full set of data. Use StandardDeviationSample to calculate the standard deviation of a subset of the full population (5.4.3.37). An example would be when the underlying data is collected on an exception basis versus sampled from the data source.

Table 50 – StandardDeviationPopulation Aggregate summary

StandardDeviationPopulation Aggregate Characteristics

Type

Calculated

Data Type

Double

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Always Good

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

No special handing required

No End Bound

No special handing required

Bound Bad

No special handing required

Bound Uncertain

No special handing required

The VariancePopulation Aggregate defined in Table 51 retrieves the square of the standard deviation. Its behaviour is the same as the StandardDeviationPopulation Aggregate. Unless otherwise indicated, qualities are Good, Calculated.

This calculation is for a full population where the calculation is done on the full set of data. Use VarianceSample to calculate the variance of a subset of the full population (5.4.3.38).

Table 51 – VariancePopulation Aggregate summary

VariancePopulation Aggregate Characteristics

Type

Calculated

Data Type

Double

Use Bounds

None

Timestamp

StartTime

StatusCode Calculations

Calculation Method

Custom

Always Good

Partial

Set Sometimes

If an interval is not a complete interval

Calculated

Set Always

Interpolated

Not Set

Raw

Not Set

Multi Value

Not Set

StatusCode Common Special Cases

Before Start of Data

Bad_NoData

After End of Data

Bad_NoData

No Start Bound

No special handing required

No End Bound

No special handing required

Bound Bad

No special handing required

Bound Uncertain

No special handing required