From XBRLWiki

CEN Workshop Agreement

Status: Working Group Working Draft

CEN WS XBRL Experts: Thierry Declerck (DFKI), Roland Hommes (Rhocon), Katrin Heinze (Deutsche Bundesbank)

Editing rules

Editorial comments should be highlighted as follows: A comment

Text or rules in discussion (white): Some text

Text or rules already aligned (green): Some text

Text or rules to be deleted (red): Some text

Text to be delivered (blue): Some text

Contents 1 Foreword 2 Introduction 2.1 Objective 2.2 Target Audience 2.3 Relationship to Other Work 3 Scope 4 Normative references 5 Terms and definitions 6 Data Point Meta model 6.1 Structural Perspective 6.1.1 DataPointModel 6.1.2 PublicElement 6.1.3 DictionaryElement 6.1.4 Framework 6.1.5 Table 6.1.6 TableGroup 6.1.7 Hierarchy 6.1.8 Taxonomy 6.1.9 Module 6.1.10 Dimension 6.1.11 Domain 6.1.12 EnumerableDimension 6.1.13 NonEnumerableDimension 6.1.14 Member 6.1.14.1 DefinedMember 6.1.14.2 NonDefinedMember 6.1.15 DimensionedElement 6.1.16 Family 6.2 Versioning Perspective 6.3 Dimension Validation Perspective 6.3.1 TableCube 6.3.2 DataPoint 6.4 Hierarchical Perspective 6.4.1 HierarchyRelationship 6.4.2 RuleRelationship 6.4.3 PresentationRelationship 6.5 Presentation Perspective 6.5.1 Axis 6.5.2 Row 6.5.3 Column 6.5.4 Sheet 6.5.5 Cell 6.6 Data Point Metamodel Constraints 6.6.1 General constraints 6.6.2 Data warehouse specific constraints

Foreword

Some text

Introduction

Data Point Modeling is a data oriented methodical procedure to create semantic and multidimensional models that reflect the reporting requirements of European supervisors. Reporting requirements are defined by regulations and represented in tables. First Data Point Models were developed in 2009 to describe the data in a redundancy-free, consistent and unambiguous way.

A Data Point Model reflects semantic and multidimensional aspects of data modeling. Semantic models are used to ease the communication between domain experts and IT specialists. Whereas formal models are defined for technical purposes semantic models are defined from a viewpoint of a domain user. They can contain definitions, documentations and explanations. Domain experts decide which objects are relevant and which relations exists between the objects of the model. Semantic models are independent of any physical implementation.

The characteristic of multidimensional models is the division of data in quantitative and qualitative aspects. Parameters that are meas-ured in figures (also known as metrics) are quantitative aspects that often build the basis of data analyses. Qualitative aspects provide a closer description for these parameters. Data objects based on multidimensional models are referred to as facts. Fact attributes are the quantitative aspects of a fact and dimensions are the synonym of the qualitative aspects of a fact.

Data Point Models should enhance the understanding of the data requirements for the reporting entities by providing information to cor-relations that exceed the information given only by table structures. The main challenge in data modeling is the identification of implicit information given in tables and its transformation in an explicit and logical model. As Data Points Models are semantic models they are created by banking specialists who are highly skilled in understanding supervisory reporting frameworks.

The document intends to support the communication between supervisory experts and IT experts by introducing the concept of data point modeling and its underlying terms. Data Point Models remain as semantic models at first technologically-neutral but they are used by IT specialists (1) for generating data formats for the reporting process or (2) for designing multidimensional database structures for the analysis of supervisory data.

This guidance is in the form of notes in association with the pertaining requirements clause and uses the terms “MUST” (strong recommendation), “SHOULD” (recommendation) and “MAY” (possibility). Organizations wishing to implement this CWA (CEN Workshop Agreement) would be expected to consider all recommendations where the terms "MUST" and “SHOULD” are used.

Objective

A Data Point Model consists of objects that reflect the supervisory data and its relations among each other that can be communicated and understood by computers. The objects of a data point model described in this document facilitate the ease of understanding of the data structure for technicians and reflects the rules to be met when using a data point model as basis for the generation of a data format or as basis for analysis purposes.

Target Audience

This document is being created to support Information Technology (IT) experts in the transfer of content from regulatory reporting to IT systems. It assumes that the reader has a working knowledge of the XBRL 2.1 and the XBRL Dimensions 1.0 Specifications as Data Point Models are being used as basis for generating XBRL taxonomies. Furthermore basic knowledge about Business Intelligence is assumed to understand the rules to be followed when designing multidimensional database structure for data warehouses.

Relationship to Other Work

Some text

Scope

The Data Point Methodology has been defined for the creation of data point models in the context of European supervisory reporting. Data Point Models are published by an European supervisory authority. To reflect the defined structures in a machine-readable form they can be accompanied by an XBRL taxonomy.

Normative references

Some text

Terms and definitions

There are no formal definitions that are taken from other documents. Comment-04

Data Point Meta model

The data point meta model provides (1) the components for the construction of a formal model that describes sets of data points relevant to European supervisory reporting frameworks, (2) rules on how to combine these components and (3) the meaning (semantic) of the components and relations. Similar to a model construction kit for toys it provides the modelling principles with all characteristics available for use by the modeller. A UML class diagram is used to provide the syntax and semantic to define the meta model for data points by showing the relevant classes and their attributes.

Structural Perspective

DataPointModel

A DataPointModel (DPM) defines structures of data describing the characteristics of the information exchanged in the context of supervisory reporting processes. A DPM consists of a dictionary of business concepts and their properties which are represented in tables. It identifies the content of each DataPoint by its granular components with a semantic meaning and its relation to other data points.

From an IT perspective a DPM can be interpreted by IT applications which enable (1) a generation of data formats for the reporting process or (2) the design of multidimensional database structures for the analysis of supervisory data, i.e., in data warehouses.

Contained elements: Public Element

References:

meta class	multiplicity	description
PublicElement	one or more	References the collection of PublicElements owned by a DataPointModel.

PublicElement

A PublicElement is a generalization of a concept of the model. It is identified by a code and consists of an appropriate label. PublicElements have two additional attributes giving information about the date of creation and modification. Each PublicElement is owned by an institution or an organization. The owner needs to be made explicit in the DataPointModel. PublicElements are abstract and need to be specified by its concrete sub classes like Frameworks, Tables etc.

References:

meta class	multiplicity	description
DataPointModel	exactly one	References the DataPointModel owning the collection of PublicElements.

DictionaryElement

DictionaryElement is an abstract class of elements that build the basis of the core concepts of a DataPointModel like DimensionedElements, Dimensions, Domains and DefinedMembers. They are derived from PublicElements and may define a currency period to support versioning and enable a filtering of obsolete elements by applications. The currency period is defined by two optional attributes validFrom and validTo which should ease the maintenance of elements of the DataPointModel in the course of time.

Comment-06

Superclass: PublicElement

Framework

A Framework is a business term common to a group of business users that consists of reporting regulations for a Domain specific scope of information.
The information requirements of a Framework are structured through Tables to ease the understanding for the reporting entities that are obliged to submit the information to their supervisor. Business rules to be met by the reporting entities are also defined in the reporting regulations. Some rules are incorporated in the Table design. E.g. the detailed information which is being part of a summation.

A DPM can refer to one or more supervisory Frameworks. Information should be given to which Framework the defined elements of the DPM refer to.

Superclass: PublicElement

Table

A Table reflects the structure of a business template or represent an individual view on supervisory data based on a specific business context. A business template is a collection of supervisory data ordered in a representation that is fitting to the business domain. On basis of business templates users are able to understand the context and relationships between the required data. As business templates are used for the communication between supervisors and reporting entities DataPoints are grouped in Tables in a DPM to reconstruct the business templates for presentational purposes.

a DPM must contain presentational information to reconstruct theses defined tables.

A Table consists of the combination of one, two or three Axes which form Columns (in the X-Axis), Rows (in the Y-Axis) and Sheets (in the Z-Axis). A duplication of Tables is indicated by two or more Sheets. Axes can be build on basis of a set of DictionaryElements that could be already defined in a Hierarchy. The combination of the DictionaryElements in each Axis define a Cartesian product which represents the set of DataPoints reflected in a Table. Tables are normalized from a dimensional perspective because a DictionaryElement can only be associated to one Axis.

Superclass: PublicElement

TableGroup

A TableGroup is a set of Tables that represents a business template. A TableGroup is being created when a business template defines more than one table to reflect the business context. A TableGroup needs also to be created when the business template refers to the same dimension-member combinations in more than one axes. The business template is to be split in two or more tables to prevent that the same dimenion is associated to a Data Point more than once.

Superclass: PublicElement

Hierarchy

Members as well as DimensionedElements can be arranged in hierarchies to represent the relationships to one another. In mathematical terms a hierarchy is a rooted tree that provides the information if a member is at top level, below another member or at the same level. Financial information is often split up in different segmental breakdowns which represent Dimensions in multidimensional terms. If the Members of a Dimension share the same level of detail, they could be represented as a flat list. But often the Members relate to each other, i.e. in a parent-child relationship, and so they form natural hierarchies. The information about the location of a Member in a Hierarchy of a Dimension improves its understanding. Furthermore, Hierarchies can be used to define rules for calculations or aggregations. In the DPM a Hierarchy forms are sets of Members of an explicit domain arranged in a hierarchical disposition.

Superclass: PublicElement

Taxonomy

A Taxonomy combines the components for a version of the DPM for a given period in time. Its currency period is defined by the attributes validFrom and validTo. By creating a relation between Taxonomy and DictionaryElements, Tables and Hierarchies a set of valid DPM components are being created. PublicElements like Table and Hierarchy that have not been modified since the last version of Taxonomy can be reused.

Superclass: PublicElement

Module

A Module is a group of TableCubes that carry relevant identical semantics and may serve the reporting process. Modules define sets of business information that should be reported together, i.e. to conduct validation rules that are defined across TableCubes.

Superclass: PublicElement

Dimension

A Dimension is a data set to one characteristic area which is composed of individual and non-overlapping data elements. In the context of a DataPointModel Dimensions are used to group information in a meaningful way. Dimensions are used to define "by" conditions and provide structured information to describe a DataPoint in detail. A Dimension can refer to a enumerable Domain with a definite number of elements or an innumerable Domain where the Members are defined by a data type and some additional constraints. Whereas the DimensionedElement represents the quantitative aspects, the qualitative aspects are described by Dimensions. The values given to Dimensions are called Members.

Superclass: DictionaryElement

References:

meta class	multiplicity	description
Domain	one or more	References a collection of Domains associated with a Dimension.
Family	zero or more	References the Families owning a collection of Dimensions.

Domain

A Domain is a classification system to categorize items that share a common semantic identity. A Domain provides therefore an unambiguous collection of items in a value range. The items of a Domain can have a definite, and therefore countable, number of items, or an infinite number of elements that follow a specific (syntax) pattern.

Contained elements: Member

References:

meta class	multiplicity	description
Dimension	exactly one	References the Dimension associated with this Domain.

EnumerableDimension

An EnumerableDimension is a subclass of Dimension that specifies a finite number of Members.

Superclass: DictionaryElement, Dimension
Contained elements: DefinedMember

References:

meta class	multiplicity	description
DefinedMember	one or more	References the set of DefinedMembers owned by an EnumerableDimension.

NonEnumerableDimension

A NonEnumerableDimension is a subclass of Dimension that specifies an undefined number of Members in the Dimension. The NonEnumerableDimension defines syntactic constraints on the values of the Members, i.e. a dataType or a specific pattern.

Superclass: DictionaryElement, Dimension
Contained elements: NonDefinedMember

References:

meta class	multiplicity	description
NonDefinedMember	one or more	References the set of NonDefinedMembers owned by an NonEnumerableDimension.

Member

A Member is the actual value that is given to a Dimension. Members can be grouped in Domains. Members in a Domain share certain semantic identity, just like the set of Members in a Dimension.

DefinedMember

A DefinedMember is discrete and countable. These Members can be explicitly listed in an enumeration. The metaclass DefinedMember has an optional attribute default.

Superclass: DictionaryElement, Member

References:

meta class	multiplicity	description
EnumerableDimension	exactly one	References the EnumerableDimension owning the collection of DefinedMembers.

NonDefinedMember

A NonDefinedMember is defined by syntactic constraints on a possible value, not the value itself.

Superclass: Member

References:

meta class	multiplicity	description
NonEnumerableDimension	exactly one	References the NonEnumerableDimension owning the collection of NonDefinedMembers.

DimensionedElement

DimensionedElements represent the nature of the data with a fixed and unchangeable meaning. DimensionedElements are strongly related to the underlying data type. Mostly they are numeric and quantitatively measurable to be used for calculations and aggregations but they can be also reflect boolean or date values. A DimensionedElement is the essential part of a DataPoint that can also refer to zero or more Dimensions with its according set of Members.

• The attribute dataType establishes the set of possible values of the facts reported according to that metric: monetary information, percentages, dates, texts…
• The attribute periodType defines whether the property / amount to be measured corresponds to a specific moment in time (instant type) or whether its nature requires it to be obtained by taking measures during an interval of time (duration type).

Superclass: DictionaryElement

Family

Families are groups of Dimensions relevant for presentation or querying purposes.

Superclass: DictionaryElement
Contained elements: Dimension

References:

meta class	multiplicity	description
Dimension	zero or more	References the set of Dimensions owned by a Family.

Versioning Perspective

A DataPointModel combines the reporting regulations for several specific scopes of information (solvency information, financial information…) summarized in one or more Frameworks. The name of a Framework is stable in time but the BusinessTemplates referring to a Framework change according to amended reporting requirements in the course of time. A Taxonomy represents a set of reporting requirements which are enforced by normative or legal acts for a period of time. The currency period starts with the a law becoming effective. In general a new Taxonomy version must replace the previous one so the currency period of the old one ends before the new version becomes valid. It is not allowed to have two overlapping Taxonomy versions referring to the same reporting period.

A Taxonomy consists of DictionaryElements that are valid for the currency period given by the Taxonomy. DictionaryElements which validTo date ended before the currency period start are not part of the Taxonomy. Over the course of time several Taxonomy versions exists which may refer to one Framework. In order to reduce the cost of maintenance, Tables from previously released Taxonomies that have not suffered any modification can be referred to from a new Taxonomy.

References:

meta class	referenced meta class	multiplicity	description
DataPointModel	Framework	zero or more	References the collection of Frameworks owned by a DataPointModel.	Framework	DataPointModel	exactly one	References the DataPointModel owning a collection of Frameworks.	Framework	TableGroup	zero or more	References the set of TableGroups associated with this Framework.	Framework	Table	zero or more	References the set of Tables associated with this Framework.	Taxonomy	DictionaryElement	zero or more	References the collection of valid DictionaryElements owned by a Taxonomy.	Taxonomy	Table	zero or more	References the collection of Tables owned by a Taxonomy.	DictionaryElement	Taxonomy	exactly one	References the Taxonomy owning a collection of valid DictionaryElements.	Table	Taxonomy	exactly one	References the Taxonomy owning a collection of Tables.	Table	Framework	exactly one	References the Framework associated with this Table.	Table	TableGroup	exactly one	References the TableGroup owning a collection of Tables.	TableGroup	Table	one or more	References the collection of Tables owned by a TableGroup.	TableGroup	Framework	exactly one	References the Framework associated with this TableGroup.

Dimension Validation Perspective

The dimensional validation that takes place on DataPoints is hosted by TableCubes. These TableCubes can be grouped into logical groups called Modules. The dimensional validation is formed by a DimensionedElement combined with at least one Dimension that hosts at least one Member. Each DataPoint MUST be represented in one TableCube; there can be no Dimensioned Element that has no Dimensions. Although this perspective shows that Dimensions have a relation that has '0' on its connection from a DataPoint. This is intentional. There is no rule in DPM that states that DimensionedElements cannot do without any Dimensions. It is allowed to host non dimensional DataPoints, but obviously this would not result in a dimensional validation.

TableCubes may represent multiple BusinessTemplates and vice versa, a single BusinessTemplate can be represented in multiple TableCubes, these groups may results in a Module.

TableCube

A TableCube is a set of DataPoints with its appropriate Dimensions and Members. A TableCube must be part of at least one Module. A TableCube combines DataPoints that share the same dimensionality. The same dimensionality is given when the DataPoints have the same number of Dimensions and the Dimensions of each DataPoints are equivalent. In comparison to a Table a TableCube must not contain any combination of DictionaryElements that are not allowed. Non allowed data is often marked as gray cells in viewers on BusinessTemplates.

Contained elements: DataPoint

References:

meta class	multiplicity	description
Module	exactly one	References the Module owning a set of TableCubes.
DatPoint	zero or one	References the collection of DataPoints owned by a TableCube.

DataPoint

A DataPoint is characterized by defining its basic financial meaning and specifying information of breakdowns (Hierarchies) in which it is described in different tables or paragraphs of documentation. A DataPoint can only have one DimensionedElement which holds the quantitative aspects about its dataType (e.g. text, number, percentage) and periodType (i.e. instant, duration). The qualitative aspects of a DataPoint is described by a (set of) Dimension(s) with each Dimension referring to at least one Member.

A EnumerableDimension with a DefinedMember marked as default is implicitly applied when this Dimension is not explicitly associated to a DataPoint. Example: When the TableCube has a dimensional context of 10 Dimensions but only 8 Dimensions are associated with according Members to a DataPoint then two EnumerableDimensions are implicitly included with their default DefinedMembers.

Contained elements: Dimension, DimensionedElement

References:

meta class	multiplicity	description
DimensionedElement	exactly one	References the element to be dimensioned by a set of Dimensions with their according Members.
Dimension	zero or more	References a set of Dimensions, each Dimension is linked to one Member.

Hierarchical Perspective

Another facility for validation of DataPoints (besides dimensional validation) is brought to DPM with the use of Hierarchies. But Hierarchies can also be used for presentational purposes. Hierarchies therefore have two objectives.

1. is the definition of logical and/or arithmetical relations between DictionaryElements (Eg. a total comprises of details).
   
2. is to structure DictionaryElements to increase the comprehensibility of DataPoints and their relation to each other.
   

Hierarchies are optional for DPM.

For arithmetical relationships two warnings are in place:

1. When using multiple DimensionedElements on a single Dimension that has a Hierarchy in its DefinedMembers, the required math may not be possible to perform.
2. When using non-numeric typed DimensionedElements on a single Dimension that has a Hierarchy in its DefinedMembers, the required math may not be possible to perform.

Comment-22

HierarchyRelationship

A HierarchyRelationship defines a logical relationship between a pair of DictionaryElements. One of these DictionaryElements defines the parent and the second defines the child. Both DictionaryElements are referenced by their identifiers. A HierarchyRelationship can be of the type presentation or rule.

RuleRelationship

A RuleRelationship is expressing a mathematical relationship between DimensionedElements. RuleRelationships have a sign attribute which identifies the arithmetical relationship between the two nested elements. The list of possible signs in a DPM is not determined. Examples are: + (plus sign) or - (minus sign).

PresentationRelationship

A PresentationRelationship is a Hierarchy for presentational purposes. The order attribute provides information about the ordering of childcodes within the same parentcode. All PresentationRelationships together form a tree structure to be visualized in (e.g.) an Axis of a Table.

Presentation Perspective

Data required by supervisors is described in legal normative acts and mostly reflected in bi-dimensional forms usually referred to as BusinessTemplates. In most of the cases a BusinessTemplates is represented by only one Table. Sometimes such a convenient match is not possible because there is a high degree of complexity in the Template that does not allow grouping the DataPoints in the same view as the predefined Template. A split of a BusinessTemplate in different Tables is needed from a presentation perspective. A set of Tables reflects then the data requirements defined in one BusinessTemplate. The DPM reflects the link between the BusinessTemplates and the Tables that represent their content.

A Table consists of a combination of one or more axes. To each axis a set of DictionaryElements is assigned to. The x-axis defines the Columns as horizontal arrangement whereas the y-axis represents a vertical progression of Rows in a Table. The z-axis can be interpreted as the identifier of a Sheet in a series of two-dimensional Tables with the same structure. An Axis can be also linked to one or more Hierarchies build upon DictionaryElements.

It is possible to assign HeaderLabels to an axis. They are specific to a Table and only used for presentation purposes. One Cell in a Table is a combination of one Column, one rRw and optional Sheets and hires the dimensional combinations of the Dictionary Elements linked with these axes. A Cell can represent a DataPoint in the model if it corresponds to data requirements. In the case of the Cell is not asked by a supervisor a dimensional validation ensures that the incorrect DataPoint is being identified.

Axis

An Axis is considered the vertical or horizontal line that makes up the quadrants of a coordinate plane. The vertical Axis is usually referred to as the Y-axis and the horizontal Axis is usually referred to as the X-axis. In dimensional modeling the Z-axis is considered to represent anything that doesn't apply to the X or Y axis. In DPM the Z axis can best understood as the tabular Sheets in a spreadsheet program, representing multiple slices of what the X and Y axis display. Often Z-axis content is presented as fixed parameters to the display of X and Y, usually represented in the graph header(s) and footer(s).

Row

A Row is the representation of what the Y-axis is made up of: Each of the individual ordinates are represented on a single Row.

Column

A Column is the representation of what the X-axis is made up of: Each of the individual ordinates are represented on a single Column.

Sheet

A Sheet is the representation of what the Z-axis is made up of: Each of the individual ordinates CAN be represented on a single Sheet.

Cell

A Cell is the coordinate where the ordinates of X and Y axes meet. It represents a place where a single (fact)value can be shown or entered.

Data Point Metamodel Constraints

General constraints

• 1.01   Each PublicElement MUST have a code.
  For each PublicElement a technical code MUST be defined.

context PublicElement inv: 
    self.code->size() = 1

• 1.02   Each PublicElement MUST have at least one label.
  At least one Label for a PublicElement MUST be given which provides the human readable meaning of this element.

context PublicElement inv: 
    self.label->size() >= 1

• 1.03   All PublicElements belonging to a DPM MUST have unique codes.
  Using a code on more than one PublicElement is not allowed.

context PublicElement inv: 
    self.allInstances()->isUnique(p : PublicElement | p.code)

• 1.04   All labels of the set of PublicElements MUST be unique.
  Creating more than one label refering to two different PublicElements is not allowed.

context PublicElement inv: 
    self.allInstances()->isUnique(p : PublicElement | p.label)

• 1.05   Each DimensionedElement MUST define a data type and a period type.
  Each DimensionedElement is to be determined by a data type and a period type.

context DimensionedElement inv: 
    self.dataType->size() = 1 
    and self.periodType->size() = 1

• 1.06   Each DefinedMember MUST be referenced by an Enumerable Domain.
  Defined Members need a reference to an EnumerableDomain so that they are able to be used for the definition of DataPoints.

context DataPointModel inv: 
    self.DefinedMember->forAll(m | m.EnumerableDomain->notEmpty())

• 1.07   Each DefinedMember MUST be part of a Hierarchy.
  In some cases breakdowns represent certain business notion rather than disagregation (e.g. Solo, IFRS consolidation, CRD consolidation). In such case the Hierarchy would be just a flat list of Members.
• 1.08   Each EnumerableDomain MUST have one default Member.
  Some explanation.

context EnumerableDomain inv: 
    self.DefinedMember->select(isDefault = true)->size() = 1 

• 1.09   Each EnumerableDomain MUST refer to one or more Hierarchies.
  Some explanation.
• 1.10   There MUST NOT be a doubling of Members in different Domains.
  Some explanation.
• 1.11   Each Dimension MUST point to one Domain.
  Some explanation.
• 1.12   Each Hierarchy MUST have only one root Member.
  The root of each Hierarchy is an EnumerableDomain. The DefinedMembers should be attached underneath.
• 1.13   A Member MUST be unique in a Hierarchy.
  The same Member MUST NOT be used twice in the same Hierarchy.

Data warehouse specific constraints