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2 Classes of duplicates
2.1 Complete duplicates
2.2 Consistent duplicates
2.3 Multi-language duplicates
2.4 Inconsistent duplicates
3 Issues with the XBRL v2.1 definition of duplicates
4 Duplicates in Inline XBRL: processor behaviour
5 Issues with duplicates
5.1 Calculation consistency checking
5.1.1 Calculation consistency checks in Inline XBRL
5.2 Formula processing
6 Duplicates in XBRL: Recommended approach
7 Duplicates in Inline XBRL
7.1 Complete duplicates in Inline XBRL
7.2 Consistent duplicates in Inline XBRL
7.3 Inconsistent duplicates in Inline XBRL
7.4 Recommended approach
XBRL reports may include duplicate facts, that is, two or more facts that purport to provide the same piece of information. The reported values may be the same, or different. Where the values are different, this may or may not be indicative of a problem in the data. For example, the same information reported at differing levels of precision would yield different literal values, but is not indicative of an error in the data.
The XBRL v2.1 specification [XBRL 2.1] provides a definition of duplicate facts, but aside from specifying their impact on calculation checks, it does not prohibit or even discourage their use. Further, it does not make any distinction between different classes of duplicate facts based on the consistency of their values.
Whilst preparer guidance for the creation of XBRL reports usually discourages or prohibits the use of duplicate facts, best practice for the creation of Inline XBRL [Inline XBRL Specification] reports can legimately lead to duplicates. It is not uncommon for a report to include the same piece of information multiple times, and tagging guidance for Inline XBRL typically requires all such occurrences to be tagged. In some cases, such facts may be de-duplicated when the document is transformed into XBRL, but in other cases duplicate facts will be present in the resulting XBRL.
This document provides definitions for different classes of duplicates, clarifies the behaviour required of Inline XBRL processors with respect to duplicates, and provides recommendations for how duplicates should be handled in a filing system.
This section provides definitions for different types of duplicates that may be encountered. All of these would be considered duplicates under the XBRL v2.1 definition of duplicate items.
It is expected that the forthcoming Open Information Model specification will provide new, formal definitions of these classes of duplicates based on "aspects", rather than the syntactical definitions provided by the XBRL v2.1 specification. This working group note will be updated to reflect this.
Facts that fulfil the XBRL v2.1 definition of duplicate items, and which additionally:
It should be noted that value equality refers to equality in the value space for the corresponding datatype, rather than requiring the same lexical representation. For example, "1.00" and "1.0" would be considered equal for a decimal value.
Facts that fulfil the XBRL v2.1 definition of duplicate items, and which additionally:
It should be noted that numeric facts that are Complete Duplicates are also considerd to be Consistent Duplicates.
Facts that fulfil the XBRL v2.1 definition of duplicate items, but which are
based on certain string item types, and which are differentiated by having
unique effective values of the
@xml:lang attribute. The string
item types included in this definition are stringItemType,
normalizedStringItemType, and types derived
from them. It should be noted that the effective language for a particular
element may be inherited from an
@xml:lang attribute appearing on
an ancestor element.
Such duplicates may provide multi-language translations of a fact, but there is no automatable way to determine if the statements being made in different languages are equivalent. As such, it is not possible to identify them as being either consistent or inconsistent.
The XBRL v2.1 definition of duplicates is imperfect, as it relies on string
equality when comparing the content of elements in the context definition.
This means that QNames values that use different namespace prefixes to refer to
the same namespace would not be considered the same. In the general case, a
QName-aware comparison may not be possible, as it requires XML type information
which may not be available for the contents of
<scenario> elements. For implementations that are following the
recommendations made in the Use of Dimensions Working Group Note [DIMENSIONS-USE-WGN], where the only content of these elements will be
XBRL Dimensions, a more robust QName-aware comparison can and should be used.
This anomaly will be removed with the switch to aspect-based definitions described above.
The Inline XBRL specification [Inline XBRL Specification] allows, but does not require, processors to de-duplicate facts that are complete duplicates when transforming from Inline XBRL to XBRL. Consistent (but not complete) duplicates and inconsistent duplicates will not be be de-duplicated by an Inline XBRL processor, and so will always be included in the resulting XBRL.
As such, XBRL that is produced by an Inline XBRL processor may contain duplicates of all categories described above, with the exact handling of complete duplicates being processor-dependent. More details on the behaviour relating to duplicates can be found in the Inline XBRL Primer [Inline XBRL Primer].
The presence of duplicates in an XBRL document can create problems for processing, storage and analysis of the data.
The XBRL v2.1 specification provides the "summation-item" arcrole that can be used to define simple calculation relationships between concepts that will be checked against corresponding facts in an XBRL report. Such calculation checks are only performed if neither the total, nor any of the contributing items, have duplicates; the presence of any duplicates effectively disables calculation checks.
A further issue is that the XBRL v2.1 specification requires that calculations are checked to be correct to the declared precision of the total (summation item). This can be problematic if the total item is reported multiple times at different precisions. For example, the item may be presented on face financial statements at a lower precision to how it is presented in a detailed note. If the contributing items are also stated at the lower precision, the calculation check may only pass when the lower precision version of the total fact is used.
Unfortunately, there is no good solution to this problem: including both facts would disable the check, and including only the lower precision fact loses information, and may have knock-on effects if that fact is itself a contributing item to another calculation check. Implementers should be aware of the limitation of calculation checks in this regard.
The facts in the example below represent a consistent calculation.
Item1: 2.6 (reported as 2600000 decimals = -5)
Item2: 3.1 (reported as 3100000 decimals = -5)
Total: 5.7 (reported as 5700000 decimals = -5)
If the total item were also reported elsewhere to a greater a precision, for example as 5,722,000 (decimals = -3), this creates a problem for the calculation. Including both versions of the facts (as consistent duplicates) would disable the calculation check. Including only the most precise (5,722,000) would cause the calculation to be checked to a precision of decimals = -3, and thus fail. Including only the less precise fact would represent a loss of information.
As de-duplication of facts in an Inline XBRL document is, to some extent, implementation dependent, this in turn means that the results of checking of "summation-item" relationships against XBRL produced via an Inline XBRL transform are implementation dependent.
Even where an Inline XBRL processor performs de-duplication to the maximum extent allowed by the specification, the use of Inline XBRL may still yield consistent or inconsistent duplicates in the resulting XBRL. The presence of either would effectively disable any calculation checks performed on these facts.
If summation-item checks are being used in combination with Inline XBRL, it is recommended that a separate de-duplication process is used prior to applying such checks.
Variables in formula rules will "bind" to each occurrence of a duplicate fact, causing the rules to evaluate for each combination of the duplicate facts involved in the rule. This may have an adverse effect on performance, and may cause repetition of any detected errors.
For example, take a trivial rule that checks the equality of two facts, A and B:
A == B
If A and B are both reported twice, as duplicates A1 and A2, and B1 and B2, then the rule will be evaluated four times, once for each combination of facts:
A1 == B1
A1 == B2
A2 == B1
A2 == B2
Clearly, if more duplicate facts are involved, this has the potential to lead to a very large number of unnecessary evaluations, and a large number of repeated results.
The presence of duplicates adds significant complexity to the storage of facts in systems such as databases as, in general, individual facts can no longer be uniquely identified by the combination of their aspects (i.e. the combination of concept, period, entity, dimensions, etc.)
If Inconsistent Duplicates are rejected, and Complete Duplicates are de-duplicated, then any remaining Consistent and Multi-Language Duplicates can be uniquely identified provided that precision and language are treated as aspects. However, the possibility that a given query on the storage system may result in multiple numeric facts differentiated only by their precision is likely to add complexity to any further processing.
Where Inline XBRL is not used, it is typically possible to avoid the issues relating to duplicates by simply using filing rules to prohibit the inclusion of any duplicates at all:
Inline XBRL introduces "legitimate" reasons for the inclusion of duplicates. In many reporting scenarios, it is common for the same piece of information to be presented multiple times in a human-readable presentation of the report. For example, the figure for revenue may appear on the main financial statements as well as in a note giving a detailed breakdown.
It is generally considered best practice to tag all figures in an Inline XBRL document, as this makes it easier to spot untagged figures, and it makes it possible for consumers to navigate effectively between XBRL facts and the locations in which they were reported in the presentation.
As described above, whether multiple tagging of complete duplicates in Inline XBRL results in duplicates in the resulting XBRL is processor-dependent.
It is possible that the same information is presented to a different precision in different places. In this case, even using an Inline XBRL processor that de-duplicates to the maximum extent allowed by the specification, consistent duplicates will be present in the resulting XBRL.
It is also possible that the same fact is reported with different values that are not consistent, giving inconsistent duplicates in the resulting XBRL. In the case of numeric facts, this is almost certainly indicative of an error, either in the underlying presentation or in the way that it has been tagged.
In the case of non-numeric facts, it is possible that inconsistent duplicates would result from strings that would be considered equivalent from a business perspective. For example, when reporting the name of a director, the forename might be abbreviated in one place but not another (e.g. "J. Smith" vs "John Smith"). Similarly, differences in capitalisation and spacing would result in duplicates that are technically inconsistent, but which might be considered acceptable from a business perspective.
Clearly, the ideal solution would be to have all such facts presented in exactly the same manner, so that all occurrences can be tagged without introducing inconsistent duplicates. In practice, the document production workflow may make this impractical, and in this case, the benefits of completeness of tagging may be outweighed by the complexities created by having inconsistent duplicates in the document.
The following recommendations are made for dealing with duplicates in Inline XBRL:
If completeness of tagging is considered critical, then an alternative approach would be to only reject numeric, inconsistent duplicates, and accept that inconsistent non-numeric duplicates may be present in the XBRL.
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